cybersecurity topics for research

Research Topics & Ideas: Cybersecurity

50 Topic Ideas To Kickstart Your Research

If you’re just starting out exploring cybersecurity-related topics for your dissertation, thesis or research project, you’ve come to the right place. In this post, we’ll help kickstart your research by providing a hearty list of cybersecurity-related research topics and ideas , including examples from recent studies.

PS – This is just the start…

We know it’s exciting to run through a list of research topics, but please keep in mind that this list is just a starting point . These topic ideas provided here are intentionally broad and generic , so keep in mind that you will need to develop them further. Nevertheless, they should inspire some ideas for your project.

To develop a suitable research topic, you’ll need to identify a clear and convincing research gap , and a viable plan to fill that gap. If this sounds foreign to you, check out our free research topic webinar that explores how to find and refine a high-quality research topic, from scratch. Alternatively, consider our 1-on-1 coaching service .

Cybersecurity-Related Research Topics

• Developing machine learning algorithms for early detection of cybersecurity threats.
• The use of artificial intelligence in optimizing network traffic for telecommunication companies.
• Investigating the impact of quantum computing on existing encryption methods.
• The application of blockchain technology in securing Internet of Things (IoT) devices.
• Developing efficient data mining techniques for large-scale social media analytics.
• The role of virtual reality in enhancing online education platforms.
• Investigating the effectiveness of various algorithms in reducing energy consumption in data centers.
• The impact of edge computing on the performance of mobile applications in remote areas.
• The application of computer vision techniques in automated medical diagnostics.
• Developing natural language processing tools for sentiment analysis in customer service.
• The use of augmented reality for training in high-risk industries like oil and gas.
• Investigating the challenges of integrating AI into legacy enterprise systems.
• The role of IT in managing supply chain disruptions during global crises.
• Developing adaptive cybersecurity strategies for small and medium-sized enterprises.
• The impact of 5G technology on the development of smart city solutions.
• The application of machine learning in personalized e-commerce recommendations.
• Investigating the use of cloud computing in improving government service delivery.
• The role of IT in enhancing sustainability in the manufacturing sector.
• Developing advanced algorithms for autonomous vehicle navigation.
• The application of biometrics in enhancing banking security systems.
• Investigating the ethical implications of facial recognition technology.
• The role of data analytics in optimizing healthcare delivery systems.
• Developing IoT solutions for efficient energy management in smart homes.
• The impact of mobile computing on the evolution of e-health services.
• The application of IT in disaster response and management.

Cybersecurity Research Ideas (Continued)

• Assessing the security implications of quantum computing on modern encryption methods.
• The role of artificial intelligence in detecting and preventing phishing attacks.
• Blockchain technology in secure voting systems: opportunities and challenges.
• Cybersecurity strategies for protecting smart grids from targeted attacks.
• Developing a cyber incident response framework for small to medium-sized enterprises.
• The effectiveness of behavioural biometrics in preventing identity theft.
• Securing Internet of Things (IoT) devices in healthcare: risks and solutions.
• Analysis of cyber warfare tactics and their implications on national security.
• Exploring the ethical boundaries of offensive cybersecurity measures.
• Machine learning algorithms for predicting and mitigating DDoS attacks.
• Study of cryptocurrency-related cybercrimes: patterns and prevention strategies.
• Evaluating the impact of GDPR on data breach response strategies in the EU.
• Developing enhanced security protocols for mobile banking applications.
• An examination of cyber espionage tactics and countermeasures.
• The role of human error in cybersecurity breaches: a behavioural analysis.
• Investigating the use of deep fakes in cyber fraud: detection and prevention.
• Cloud computing security: managing risks in multi-tenant environments.
• Next-generation firewalls: evaluating performance and security features.
• The impact of 5G technology on cybersecurity strategies and policies.
• Secure coding practices: reducing vulnerabilities in software development.
• Assessing the role of cyber insurance in mitigating financial losses from cyber attacks.
• Implementing zero trust architecture in corporate networks: challenges and benefits.
• Ransomware attacks on critical infrastructure: case studies and defence strategies.
• Using big data analytics for proactive cyber threat intelligence.
• Evaluating the effectiveness of cybersecurity awareness training in organisations.

Recent Cybersecurity-Related Studies

While the ideas we’ve presented above are a decent starting point for finding a research topic, they are fairly generic and non-specific. So, it helps to look at actual studies in the cybersecurity space to see how this all comes together in practice.

Below, we’ve included a selection of recent studies to help refine your thinking. These are actual studies,  so they can provide some useful insight as to what a research topic looks like in practice.

• Cyber Security Vulnerability Detection Using Natural Language Processing (Singh et al., 2022)
• Security for Cloud-Native Systems with an AI-Ops Engine (Ck et al., 2022)
• Overview of Cyber Security (Yadav, 2022)
• Exploring the Top Five Evolving Threats in Cybersecurity: An In-Depth Overview (Mijwil et al., 2023)
• Cyber Security: Strategy to Security Challenges A Review (Nistane & Sharma, 2022)
• A Review Paper on Cyber Security (K & Venkatesh, 2022)
• The Significance of Machine Learning and Deep Learning Techniques in Cybersecurity: A Comprehensive Review (Mijwil, 2023)
• Towards Artificial Intelligence-Based Cybersecurity: The Practices and ChatGPT Generated Ways to Combat Cybercrime (Mijwil et al., 2023)
• ESTABLISHING CYBERSECURITY AWARENESS OF TECHNICAL SECURITY MEASURES THROUGH A SERIOUS GAME (Harding et al., 2022)
• Efficiency Evaluation of Cyber Security Based on EBM-DEA Model (Nguyen et al., 2022)
• An Overview of the Present and Future of User Authentication (Al Kabir & Elmedany, 2022)
• Cybersecurity Enterprises Policies: A Comparative Study (Mishra et al., 2022)
• The Rise of Ransomware: A Review of Attacks, Detection Techniques, and Future Challenges (Kamil et al., 2022)
• On the scale of Cyberspace and Cybersecurity (Pathan, 2022)
• Analysis of techniques and attacking pattern in cyber security approach (Sharma et al., 2022)
• Impact of Artificial Intelligence on Information Security in Business (Alawadhi et al., 2022)
• Deployment of Artificial Intelligence with Bootstrapped Meta-Learning in Cyber Security (Sasikala & Sharma, 2022)
• Optimization of Secure Coding Practices in SDLC as Part of Cybersecurity Framework (Jakimoski et al., 2022)
• CySSS ’22: 1st International Workshop on Cybersecurity and Social Sciences (Chan-Tin & Kennison, 2022)

As you can see, these research topics are a lot more focused than the generic topic ideas we presented earlier. So, for you to develop a high-quality research topic, you’ll need to get specific and laser-focused on a specific context with specific variables of interest.  In the video below, we explore some other important things you’ll need to consider when crafting your research topic.

Get 1-On-1 Help

If you’re still unsure about how to find a quality research topic, check out our Research Topic Kickstarter service, which is the perfect starting point for developing a unique, well-justified research topic.

You Might Also Like:

Submit a Comment Cancel reply

Your email address will not be published. Required fields are marked *

Save my name, email, and website in this browser for the next time I comment.

• Print Friendly

For enquiries call:

+1-469-442-0620

60+ Latest Cyber Security Research Topics in 2024

Home Blog Security 60+ Latest Cyber Security Research Topics in 2024

The concept of cybersecurity refers to cracking the security mechanisms that break in dynamic environments. Implementing Cyber Security Project topics and cybersecurity thesis topics helps overcome attacks and take mitigation approaches to security risks and threats in real-time. Undoubtedly, it focuses on events injected into the system, data, and the whole network to attack/disturb it.

The network can be attacked in various ways, including Distributed DoS, Knowledge Disruptions, Computer Viruses / Worms, and many more. Cyber-attacks are still rising, and more are waiting to harm their targeted systems and networks. Detecting Intrusions in cybersecurity has become challenging due to their Intelligence Performance. Therefore, it may negatively affect data integrity, privacy, availability, and security. 

This article aims to demonstrate the most current Cyber Security Topics for Projects and areas of research currently lacking. We will talk about cyber security research questions, cyber security topics for the project, latest research titles about cyber security.

List of Trending Cyber Security Research Topics in 2024

Digital technology has revolutionized how all businesses, large or small, work, and even governments manage their day-to-day activities, requiring organizations, corporations, and government agencies to utilize computerized systems. To protect data against online attacks or unauthorized access, cybersecurity is a priority. There are many Cyber Security Courses online where you can learn about these topics. With the rapid development of technology comes an equally rapid shift in Cyber Security Research Topics and cybersecurity trends, as data breaches, ransomware, and hacks become almost routine news items. In 2024, these will be the top cybersecurity trends.

A. Exciting Mobile Cyber Security Research Paper Topics

• The significance of continuous user authentication on mobile gadgets. 
• The efficacy of different mobile security approaches. 
• Detecting mobile phone hacking. 
• Assessing the threat of using portable devices to access banking services. 
• Cybersecurity and mobile applications. 
• The vulnerabilities in wireless mobile data exchange. 
• The rise of mobile malware. 
• The evolution of Android malware.
• How to know you’ve been hacked on mobile. 
• The impact of mobile gadgets on cybersecurity. 

B. Top Computer and Software Security Topics to Research

• Learn algorithms for data encryption 
• Concept of risk management security 
• How to develop the best Internet security software 
• What are Encrypting Viruses- How does it work? 
• How does a Ransomware attack work? 
• Scanning of malware on your PC 
• Infiltrating a Mac OS X operating system 
• What are the effects of RSA on network security ? 
• How do encrypting viruses work?
• DDoS attacks on IoT devices 

C. Trending Information Security Research Topics

• Why should people avoid sharing their details on Facebook? 
• What is the importance of unified user profiles? 
• Discuss Cookies and Privacy  
• White hat and black hat hackers 
• What are the most secure methods for ensuring data integrity? 
• Talk about the implications of Wi-Fi hacking apps on mobile phones 
• Analyze the data breaches in 2024
• Discuss digital piracy in 2024
• critical cyber-attack concepts 
• Social engineering and its importance 

D. Current Network Security Research Topics

• Data storage centralization
• Identify Malicious activity on a computer system. 
• Firewall 
• Importance of keeping updated Software  
• wireless sensor network 
• What are the effects of ad-hoc networks  
• How can a company network be safe? 
• What are Network segmentation and its applications? 
• Discuss Data Loss Prevention systems  
• Discuss various methods for establishing secure algorithms in a network. 
• Talk about two-factor authentication

E. Best Data Security Research Topics

• Importance of backup and recovery 
• Benefits of logging for applications 
• Understand physical data security 
• Importance of Cloud Security 
• In computing, the relationship between privacy and data security 
• Talk about data leaks in mobile apps 
• Discuss the effects of a black hole on a network system. 

F. Important Application Security Research Topics

• Detect Malicious Activity on Google Play Apps 
• Dangers of XSS attacks on apps 
• Discuss SQL injection attacks. 
• Insecure Deserialization Effect 
• Check Security protocols 

G. Cybersecurity Law & Ethics Research Topics

• Strict cybersecurity laws in China 
• Importance of the Cybersecurity Information Sharing Act. 
• USA, UK, and other countries' cybersecurity laws  
• Discuss The Pipeline Security Act in the United States 

H. Recent Cyberbullying Topics

• Protecting your Online Identity and Reputation 
• Online Safety 
• Sexual Harassment and Sexual Bullying 
• Dealing with Bullying 
• Stress Center for Teens 

I. Operational Security Topics

• Identify sensitive data 
• Identify possible threats 
• Analyze security threats and vulnerabilities 
• Appraise the threat level and vulnerability risk 
• Devise a plan to mitigate the threats 

J. Cybercrime Topics for a Research Paper

• Crime Prevention. 
• Criminal Specialization. 
• Drug Courts. 
• Criminal Courts. 
• Criminal Justice Ethics. 
• Capital Punishment.
• Community Corrections. 
• Criminal Law. 

Cyber Security Future Research Topics

• Developing more effective methods for detecting and responding to cyber attacks
• Investigating the role of social media in cyber security
• Examining the impact of cloud computing on cyber security
• Investigating the security implications of the Internet of Things
• Studying the effectiveness of current cyber security measures
• Identifying new cyber security threats and vulnerabilities
• Developing more effective cyber security policies
• Examining the ethical implications of cyber security

Cyber Security Topics For Research Paper

• Cyber security threats and vulnerabilities
• Cyber security incident response and management
• Cyber security risk management
• Cyber security awareness and training
• Cyber security controls and countermeasures
• Cyber security governance
• Cyber security standards
• Cyber security insurance
• Cyber security and the law
• The future of cyber security

5 Current Research Topics in Cybersecurity

Below are the latest 5 cybersecurity research topics. They are:

• Artificial Intelligence
• Digital Supply Chains
• Internet of Things
• State-Sponsored Attacks
• Working From Home

Research Area in Cyber Security

The field of cyber security is extensive and constantly evolving. Its research covers a wide range of subjects, including: 

• Quantum & Space  
• Data Privacy  
• Criminology & Law 
• AI & IoT Security
• RFID Security
• Authorisation Infrastructure
• Digital Forensics
• Autonomous Security
• Social Influence on Social Networks

How to Choose the Best Research Topics in Cyber Security

A good cybersecurity assignment heading is a skill that not everyone has, and unfortunately, not everyone has one. You might have your teacher provide you with the topics, or you might be asked to come up with your own. If you want more research topics, you can take references from Certified Ethical Hacker Certification, where you will get more hints on new topics. If you don't know where to start, here are some tips. Follow them to create compelling cybersecurity assignment topics. 

1. Brainstorm

In order to select the most appropriate heading for your cybersecurity assignment, you first need to brainstorm ideas. What specific matter do you wish to explore? In this case, come up with relevant topics about the subject and select those relevant to your issue when you use our list of topics. You can also go to cyber security-oriented websites to get some ideas. Using any blog post on the internet can prove helpful if you intend to write a research paper on security threats in 2024. Creating a brainstorming list with all the keywords and cybersecurity concepts you wish to discuss is another great way to start. Once that's done, pick the topics you feel most comfortable handling. Keep in mind to stay away from common topics as much as possible. 

2. Understanding the Background

In order to write a cybersecurity assignment, you need to identify two or three research paper topics. Obtain the necessary resources and review them to gain background information on your heading. This will also allow you to learn new terminologies that can be used in your title to enhance it. 

3. Write a Single Topic

Make sure the subject of your cybersecurity research paper doesn't fall into either extreme. Make sure the title is neither too narrow nor too broad. Topics on either extreme will be challenging to research and write about. 

4. Be Flexible

There is no rule to say that the title you choose is permanent. It is perfectly okay to change your research paper topic along the way. For example, if you find another topic on this list to better suit your research paper, consider swapping it out. 

The Layout of Cybersecurity Research Guidance

It is undeniable that usability is one of cybersecurity's most important social issues today. Increasingly, security features have become standard components of our digital environment, which pervade our lives and require both novices and experts to use them. Supported by confidentiality, integrity, and availability concerns, security features have become essential components of our digital environment.  

In order to make security features easily accessible to a wider population, these functions need to be highly usable. This is especially true in this context because poor usability typically translates into the inadequate application of cybersecurity tools and functionality, resulting in their limited effectiveness. 

Writing Tips from Expert

Additionally, a well-planned action plan and a set of useful tools are essential for delving into Cyber Security Research Topics. Not only do these topics present a vast realm of knowledge and potential innovation, but they also have paramount importance in today's digital age. Addressing the challenges and nuances of these research areas will contribute significantly to the global cybersecurity landscape, ensuring safer digital environments for all. It's crucial to approach these topics with diligence and an open mind to uncover groundbreaking insights.

• Before you begin writing your research paper, make sure you understand the assignment. 
• Your Research Paper Should Have an Engaging Topic 
• Find reputable sources by doing a little research 
• Precisely state your thesis on cybersecurity 
• A rough outline should be developed 
• Finish your paper by writing a draft 
• Make sure that your bibliography is formatted correctly and cites your sources. 

Discover the Power of ITIL 4 Foundation - Unleash the Potential of Your Business with this Cost-Effective Solution. Boost Efficiency, Streamline Processes, and Stay Ahead of the Competition. Learn More!

Studies in the literature have identified and recommended guidelines and recommendations for addressing security usability problems to provide highly usable security. The purpose of such papers is to consolidate existing design guidelines and define an initial core list that can be used for future reference in the field of Cyber Security Research Topics.

The researcher takes advantage of the opportunity to provide an up-to-date analysis of cybersecurity usability issues and evaluation techniques applied so far. As a result of this research paper, researchers and practitioners interested in cybersecurity systems who value human and social design elements are likely to find it useful. You can find KnowledgeHut’s Cyber Security courses online and take maximum advantage of them.

Frequently Asked Questions (FAQs)

Businesses and individuals are changing how they handle cybersecurity as technology changes rapidly - from cloud-based services to new IoT devices. 

Ideally, you should have read many papers and know their structure, what information they contain, and so on if you want to write something of interest to others. 

The field of cyber security is extensive and constantly evolving. Its research covers various subjects, including Quantum & Space, Data Privacy, Criminology & Law, and AI & IoT Security. 

Inmates having the right to work, transportation of concealed weapons, rape and violence in prison, verdicts on plea agreements, rehab versus reform, and how reliable are eyewitnesses? 

Mrinal Prakash

I am a B.Tech Student who blogs about various topics on cyber security and is specialized in web application security

Avail your free 1:1 mentorship session.

Something went wrong

Upcoming Cyber Security Batches & Dates

• Privacy Policy

Home » 500+ Cyber Security Research Topics

500+ Cyber Security Research Topics

Cybersecurity has become an increasingly important topic in recent years as more and more of our lives are spent online. With the rise of the digital age, there has been a corresponding increase in the number and severity of cyber attacks. As such, research into cybersecurity has become critical in order to protect individuals, businesses, and governments from these threats. In this blog post, we will explore some of the most pressing cybersecurity research topics, from the latest trends in cyber attacks to emerging technologies that can help prevent them. Whether you are a cybersecurity professional, a Master’s or Ph.D. student, or simply interested in the field, this post will provide valuable insights into the challenges and opportunities in this rapidly evolving area of study.

Cyber Security Research Topics

Cyber Security Research Topics are as follows:

• The role of machine learning in detecting cyber threats
• The impact of cloud computing on cyber security
• Cyber warfare and its effects on national security
• The rise of ransomware attacks and their prevention methods
• Evaluating the effectiveness of network intrusion detection systems
• The use of blockchain technology in enhancing cyber security
• Investigating the role of cyber security in protecting critical infrastructure
• The ethics of hacking and its implications for cyber security professionals
• Developing a secure software development lifecycle (SSDLC)
• The role of artificial intelligence in cyber security
• Evaluating the effectiveness of multi-factor authentication
• Investigating the impact of social engineering on cyber security
• The role of cyber insurance in mitigating cyber risks
• Developing secure IoT (Internet of Things) systems
• Investigating the challenges of cyber security in the healthcare industry
• Evaluating the effectiveness of penetration testing
• Investigating the impact of big data on cyber security
• The role of quantum computing in breaking current encryption methods
• Developing a secure BYOD (Bring Your Own Device) policy
• The impact of cyber security breaches on a company’s reputation
• The role of cyber security in protecting financial transactions
• Evaluating the effectiveness of anti-virus software
• The use of biometrics in enhancing cyber security
• Investigating the impact of cyber security on the supply chain
• The role of cyber security in protecting personal privacy
• Developing a secure cloud storage system
• Evaluating the effectiveness of firewall technologies
• Investigating the impact of cyber security on e-commerce
• The role of cyber security in protecting intellectual property
• Developing a secure remote access policy
• Investigating the challenges of securing mobile devices
• The role of cyber security in protecting government agencies
• Evaluating the effectiveness of cyber security training programs
• Investigating the impact of cyber security on the aviation industry
• The role of cyber security in protecting online gaming platforms
• Developing a secure password management system
• Investigating the challenges of securing smart homes
• The impact of cyber security on the automotive industry
• The role of cyber security in protecting social media platforms
• Developing a secure email system
• Evaluating the effectiveness of encryption methods
• Investigating the impact of cyber security on the hospitality industry
• The role of cyber security in protecting online education platforms
• Developing a secure backup and recovery strategy
• Investigating the challenges of securing virtual environments
• The impact of cyber security on the energy sector
• The role of cyber security in protecting online voting systems
• Developing a secure chat platform
• Investigating the impact of cyber security on the entertainment industry
• The role of cyber security in protecting online dating platforms
• Artificial Intelligence and Machine Learning in Cybersecurity
• Quantum Cryptography and Post-Quantum Cryptography
• Internet of Things (IoT) Security
• Developing a framework for cyber resilience in critical infrastructure
• Understanding the fundamentals of encryption algorithms
• Cyber security challenges for small and medium-sized businesses
• Developing secure coding practices for web applications
• Investigating the role of cyber security in protecting online privacy
• Network security protocols and their importance
• Social engineering attacks and how to prevent them
• Investigating the challenges of securing personal devices and home networks
• Developing a basic incident response plan for cyber attacks
• The impact of cyber security on the financial sector
• Understanding the role of cyber security in protecting critical infrastructure
• Mobile device security and common vulnerabilities
• Investigating the challenges of securing cloud-based systems
• Cyber security and the Internet of Things (IoT)
• Biometric authentication and its role in cyber security
• Developing secure communication protocols for online messaging platforms
• The importance of cyber security in e-commerce
• Understanding the threats and vulnerabilities associated with social media platforms
• Investigating the role of cyber security in protecting intellectual property
• The basics of malware analysis and detection
• Developing a basic cyber security awareness training program
• Understanding the threats and vulnerabilities associated with public Wi-Fi networks
• Investigating the challenges of securing online banking systems
• The importance of password management and best practices
• Cyber security and cloud computing
• Understanding the role of cyber security in protecting national security
• Investigating the challenges of securing online gaming platforms
• The basics of cyber threat intelligence
• Developing secure authentication mechanisms for online services
• The impact of cyber security on the healthcare sector
• Understanding the basics of digital forensics
• Investigating the challenges of securing smart home devices
• The role of cyber security in protecting against cyberbullying
• Developing secure file transfer protocols for sensitive information
• Understanding the challenges of securing remote work environments
• Investigating the role of cyber security in protecting against identity theft
• The basics of network intrusion detection and prevention systems
• Developing secure payment processing systems
• Understanding the role of cyber security in protecting against ransomware attacks
• Investigating the challenges of securing public transportation systems
• The basics of network segmentation and its importance in cyber security
• Developing secure user access management systems
• Understanding the challenges of securing supply chain networks
• The role of cyber security in protecting against cyber espionage
• Investigating the challenges of securing online educational platforms
• The importance of data backup and disaster recovery planning
• Developing secure email communication protocols
• Understanding the basics of threat modeling and risk assessment
• Investigating the challenges of securing online voting systems
• The role of cyber security in protecting against cyber terrorism
• Developing secure remote access protocols for corporate networks.
• Investigating the challenges of securing artificial intelligence systems
• The role of machine learning in enhancing cyber threat intelligence
• Evaluating the effectiveness of deception technologies in cyber security
• Investigating the impact of cyber security on the adoption of emerging technologies
• The role of cyber security in protecting smart cities
• Developing a risk-based approach to cyber security governance
• Investigating the impact of cyber security on economic growth and innovation
• The role of cyber security in protecting human rights in the digital age
• Developing a secure digital identity system
• Investigating the impact of cyber security on global political stability
• The role of cyber security in protecting the Internet of Things (IoT)
• Developing a secure supply chain management system
• Investigating the challenges of securing cloud-native applications
• The role of cyber security in protecting against insider threats
• Developing a secure software-defined network (SDN)
• Investigating the impact of cyber security on the adoption of mobile payments
• The role of cyber security in protecting against cyber warfare
• Developing a secure distributed ledger technology (DLT) system
• Investigating the impact of cyber security on the digital divide
• The role of cyber security in protecting against state-sponsored attacks
• Developing a secure Internet infrastructure
• Investigating the challenges of securing industrial control systems (ICS)
• Developing a secure quantum communication system
• Investigating the impact of cyber security on global trade and commerce
• Developing a secure decentralized authentication system
• Investigating the challenges of securing edge computing systems
• Developing a secure hybrid cloud system
• Investigating the impact of cyber security on the adoption of smart cities
• The role of cyber security in protecting against cyber propaganda
• Developing a secure blockchain-based voting system
• Investigating the challenges of securing cyber-physical systems (CPS)
• The role of cyber security in protecting against cyber hate speech
• Developing a secure machine learning system
• Investigating the impact of cyber security on the adoption of autonomous vehicles
• The role of cyber security in protecting against cyber stalking
• Developing a secure data-driven decision-making system
• Investigating the challenges of securing social media platforms
• The role of cyber security in protecting against cyberbullying in schools
• Developing a secure open source software ecosystem
• Investigating the impact of cyber security on the adoption of smart homes
• The role of cyber security in protecting against cyber fraud
• Developing a secure software supply chain
• Investigating the challenges of securing cloud-based healthcare systems
• The role of cyber security in protecting against cyber harassment
• Developing a secure multi-party computation system
• Investigating the impact of cyber security on the adoption of virtual and augmented reality technologies.
• Cybersecurity in Cloud Computing Environments
• Cyber Threat Intelligence and Analysis
• Blockchain Security
• Data Privacy and Protection
• Cybersecurity in Industrial Control Systems
• Mobile Device Security
• The importance of cyber security in the digital age
• The ethics of cyber security and privacy
• The role of government in regulating cyber security
• Cyber security threats and vulnerabilities in the healthcare sector
• Understanding the risks associated with social media and cyber security
• The impact of cyber security on e-commerce
• The effectiveness of cyber security awareness training programs
• The role of biometric authentication in cyber security
• The importance of password management in cyber security
• The basics of network security protocols and their importance
• The challenges of securing online gaming platforms
• The role of cyber security in protecting national security
• The impact of cyber security on the legal sector
• The ethics of cyber warfare
• The challenges of securing the Internet of Things (IoT)
• Understanding the basics of malware analysis and detection
• The challenges of securing public transportation systems
• The impact of cyber security on the insurance industry
• The role of cyber security in protecting against ransomware attacks
• The challenges of securing remote work environments
• Understanding the threats and vulnerabilities associated with social engineering attacks
• The impact of cyber security on the education sector
• Investigating the challenges of securing supply chain networks
• The challenges of securing personal devices and home networks
• The importance of secure coding practices for web applications
• The impact of cyber security on the hospitality industry
• The role of cyber security in protecting against identity theft
• The challenges of securing public Wi-Fi networks
• The importance of cyber security in protecting critical infrastructure
• The challenges of securing cloud-based storage systems
• The effectiveness of antivirus software in cyber security
• Developing secure payment processing systems.
• Cybersecurity in Healthcare
• Social Engineering and Phishing Attacks
• Cybersecurity in Autonomous Vehicles
• Cybersecurity in Smart Cities
• Cybersecurity Risk Assessment and Management
• Malware Analysis and Detection Techniques
• Cybersecurity in the Financial Sector
• Cybersecurity in Government Agencies
• Cybersecurity and Artificial Life
• Cybersecurity for Critical Infrastructure Protection
• Cybersecurity in the Education Sector
• Cybersecurity in Virtual Reality and Augmented Reality
• Cybersecurity in the Retail Industry
• Cryptocurrency Security
• Cybersecurity in Supply Chain Management
• Cybersecurity and Human Factors
• Cybersecurity in the Transportation Industry
• Cybersecurity in Gaming Environments
• Cybersecurity in Social Media Platforms
• Cybersecurity and Biometrics
• Cybersecurity and Quantum Computing
• Cybersecurity in 5G Networks
• Cybersecurity in Aviation and Aerospace Industry
• Cybersecurity in Agriculture Industry
• Cybersecurity in Space Exploration
• Cybersecurity in Military Operations
• Cybersecurity and Cloud Storage
• Cybersecurity in Software-Defined Networks
• Cybersecurity and Artificial Intelligence Ethics
• Cybersecurity and Cyber Insurance
• Cybersecurity in the Legal Industry
• Cybersecurity and Data Science
• Cybersecurity in Energy Systems
• Cybersecurity in E-commerce
• Cybersecurity in Identity Management
• Cybersecurity in Small and Medium Enterprises
• Cybersecurity in the Entertainment Industry
• Cybersecurity and the Internet of Medical Things
• Cybersecurity and the Dark Web
• Cybersecurity and Wearable Technology
• Cybersecurity in Public Safety Systems.
• Threat Intelligence for Industrial Control Systems
• Privacy Preservation in Cloud Computing
• Network Security for Critical Infrastructure
• Cryptographic Techniques for Blockchain Security
• Malware Detection and Analysis
• Cyber Threat Hunting Techniques
• Cybersecurity Risk Assessment
• Machine Learning for Cybersecurity
• Cybersecurity in Financial Institutions
• Cybersecurity for Smart Cities
• Cybersecurity in Aviation
• Cybersecurity in the Automotive Industry
• Cybersecurity in the Energy Sector
• Cybersecurity in Telecommunications
• Cybersecurity for Mobile Devices
• Biometric Authentication for Cybersecurity
• Cybersecurity for Artificial Intelligence
• Cybersecurity for Social Media Platforms
• Cybersecurity in the Gaming Industry
• Cybersecurity in the Defense Industry
• Cybersecurity for Autonomous Systems
• Cybersecurity for Quantum Computing
• Cybersecurity for Augmented Reality and Virtual Reality
• Cybersecurity in Cloud-Native Applications
• Cybersecurity for Smart Grids
• Cybersecurity in Distributed Ledger Technology
• Cybersecurity for Next-Generation Wireless Networks
• Cybersecurity for Digital Identity Management
• Cybersecurity for Open Source Software
• Cybersecurity for Smart Homes
• Cybersecurity for Smart Transportation Systems
• Cybersecurity for Cyber Physical Systems
• Cybersecurity for Critical National Infrastructure
• Cybersecurity for Smart Agriculture
• Cybersecurity for Retail Industry
• Cybersecurity for Digital Twins
• Cybersecurity for Quantum Key Distribution
• Cybersecurity for Digital Healthcare
• Cybersecurity for Smart Logistics
• Cybersecurity for Wearable Devices
• Cybersecurity for Edge Computing
• Cybersecurity for Cognitive Computing
• Cybersecurity for Industrial IoT
• Cybersecurity for Intelligent Transportation Systems
• Cybersecurity for Smart Water Management Systems
• The rise of cyber terrorism and its impact on national security
• The impact of artificial intelligence on cyber security
• Analyzing the effectiveness of biometric authentication for securing data
• The impact of social media on cyber security and privacy
• The future of cyber security in the Internet of Things (IoT) era
• The role of machine learning in detecting and preventing cyber attacks
• The effectiveness of encryption in securing sensitive data
• The impact of quantum computing on cyber security
• The rise of cyber bullying and its effects on mental health
• Investigating cyber espionage and its impact on national security
• The effectiveness of cyber insurance in mitigating cyber risks
• The role of blockchain technology in cyber security
• Investigating the effectiveness of cyber security awareness training programs
• The impact of cyber attacks on critical infrastructure
• Analyzing the effectiveness of firewalls in protecting against cyber attacks
• The impact of cyber crime on the economy
• Investigating the effectiveness of multi-factor authentication in securing data
• The future of cyber security in the age of quantum internet
• The impact of big data on cyber security
• The role of cybersecurity in the education system
• Investigating the use of deception techniques in cyber security
• The impact of cyber attacks on the healthcare industry
• The effectiveness of cyber threat intelligence in mitigating cyber risks
• The role of cyber security in protecting financial institutions
• Investigating the use of machine learning in cyber security risk assessment
• The impact of cyber attacks on the transportation industry
• The effectiveness of network segmentation in protecting against cyber attacks
• Investigating the effectiveness of biometric identification in cyber security
• The impact of cyber attacks on the hospitality industry
• The future of cyber security in the era of autonomous vehicles
• The effectiveness of intrusion detection systems in protecting against cyber attacks
• The role of cyber security in protecting small businesses
• Investigating the effectiveness of virtual private networks (VPNs) in securing data
• The impact of cyber attacks on the energy sector
• The effectiveness of cyber security regulations in mitigating cyber risks
• Investigating the use of deception technology in cyber security
• The impact of cyber attacks on the retail industry
• The effectiveness of cyber security in protecting critical infrastructure
• The role of cyber security in protecting intellectual property in the entertainment industry
• Investigating the effectiveness of intrusion prevention systems in protecting against cyber attacks
• The impact of cyber attacks on the aerospace industry
• The future of cyber security in the era of quantum computing
• The effectiveness of cyber security in protecting against ransomware attacks
• The role of cyber security in protecting personal and sensitive data
• Investigating the effectiveness of cloud security solutions in protecting against cyber attacks
• The impact of cyber attacks on the manufacturing industry
• The effective cyber security and the future of e-votingness of cyber security in protecting against social engineering attacks
• Investigating the effectiveness of end-to-end encryption in securing data
• The impact of cyber attacks on the insurance industry
• The future of cyber security in the era of artificial intelligence
• The effectiveness of cyber security in protecting against distributed denial-of-service (DDoS) attacks
• The role of cyber security in protecting against phishing attacks
• Investigating the effectiveness of user behavior analytics
• The impact of emerging technologies on cyber security
• Developing a framework for cyber threat intelligence
• The effectiveness of current cyber security measures
• Cyber security and data privacy in the age of big data
• Cloud security and virtualization technologies
• Cryptography and its role in cyber security
• Cyber security in critical infrastructure protection
• Cyber security in the Internet of Things (IoT)
• Cyber security in e-commerce and online payment systems
• Cyber security and the future of digital currencies
• The impact of social engineering on cyber security
• Cyber security and ethical hacking
• Cyber security challenges in the healthcare industry
• Cyber security and digital forensics
• Cyber security in the financial sector
• Cyber security in the transportation industry
• The impact of artificial intelligence on cyber security risks
• Cyber security and mobile devices
• Cyber security in the energy sector
• Cyber security and supply chain management
• The role of machine learning in cyber security
• Cyber security in the defense sector
• The impact of the Dark Web on cyber security
• Cyber security in social media and online communities
• Cyber security challenges in the gaming industry
• Cyber security and cloud-based applications
• The role of blockchain in cyber security
• Cyber security and the future of autonomous vehicles
• Cyber security in the education sector
• Cyber security in the aviation industry
• The impact of 5G on cyber security
• Cyber security and insider threats
• Cyber security and the legal system
• The impact of cyber security on business operations
• Cyber security and the role of human behavior
• Cyber security in the hospitality industry
• The impact of cyber security on national security
• Cyber security and the use of biometrics
• Cyber security and the role of social media influencers
• The impact of cyber security on small and medium-sized enterprises
• Cyber security and cyber insurance
• The impact of cyber security on the job market
• Cyber security and international relations
• Cyber security and the role of government policies
• The impact of cyber security on privacy laws
• Cyber security in the media and entertainment industry
• The role of cyber security in digital marketing
• Cyber security and the role of cybersecurity professionals
• Cyber security in the retail industry
• The impact of cyber security on the stock market
• Cyber security and intellectual property protection
• Cyber security and online dating
• The impact of cyber security on healthcare innovation
• Cyber security and the future of e-voting
• Cyber security and the role of open source software
• Cyber security and the use of social engineering in cyber attacks
• The impact of cyber security on the aviation industry
• Cyber security and the role of cyber security awareness training
• Cyber security and the role of cybersecurity standards and best practices
• Cyber security in the legal industry
• The impact of cyber security on human rights
• Cyber security and the role of public-private partnerships
• Cyber security and the future of e-learning
• Cyber security and the role of mobile applications
• The impact of cyber security on environmental sustainability
• Cyber security and the role of threat intelligence sharing
• Cyber security and the future of smart homes
• Cyber security and the role of cybersecurity certifications
• The impact of cyber security on international trade
• Cyber security and the role of cyber security auditing

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

You may also like

200+ Funny Research Topics

500+ Sports Research Topics

500+ Environmental Research Topics

500+ Economics Research Topics

500+ Physics Research Topics

500+ Google Scholar Research Topics

List of 78 Top Cyber Security Topics for Research

Table of contents

• 1 How To Choose The Best Cyber Security Research Topics
• 2 📚10 Cyber Security Topics For Research Paper
• 3 📱Mobile Cyber Security Research Paper Topics
• 4 🕵Top 10 Cyber Security Topics
• 5 👨‍💻Cyber Security Research Topics 2023
• 6 🔎Best Cyber Security Research Topics
• 7 👨‍🔬Cyber Security Future Research Topics
• 8 📑Cyber Security Topics For Research Paper
• 9 👩‍💻Cyber Security Topics on Computer and Software

There are many reasons to choose cyber security research topics for writing purposes. First, cyber security is a growing field, with many new and exciting developments happening all the time. This makes it an ideal topic to write about, as there is always something new to learn and discuss. Second, cyber security research can be used to improve the security of your own computer systems. By understanding the latest threats and vulnerabilities, you can make your systems more secure and less likely to be compromised. Third, writing about cyber security can help raise awareness about the importance of cyber security. By educating others about the dangers of cyber attacks and the importance of protecting their computers, you can help make the internet a safer place for everyone.

How To Choose The Best Cyber Security Research Topics

When it comes to choosing research paper topics on cyber security, there are a few things to consider. First, it is important to make sure that the topic is relevant and timely. Cyber security is an ever-changing field, so it is important to choose a topic that will be relevant for years to come. Second, it is important to choose a topic that is interesting and engaging. Cybersecurity can be a dry topic, so it is important to choose a topic that will keep readers engaged. Finally, it is important to choose a topic that is researchable. There are a lot of cyber security topics out there, but not all of them are easy to research. Make sure to choose a topic that has plenty of information available.

• Identify your audience.
• Define your research goals.
• Choose a topic that is both interesting and relevant to your audience.
• Do some preliminary research to make sure there is enough information available on your chosen topic.
• Make sure your topic is narrow enough to be covered in a single research paper.

📚10 Cyber Security Topics For Research Paper

• The Importance of Cyber Security
• The Evolution of Cyber Security
• The Future of Cyber Security
• The Impact of Cyber Security on Business
• The Role of Cyber Security in National Security
• The Challenges of Cyber Security
• The Costs of Cyber Security
• The Benefits of Cyber Security
• The Risks of Cyber Security
• The Implications of Cyber Security

📱Mobile Cyber Security Research Paper Topics

• Mobile device security: How to protect your mobile device from cyber attacks.
• The rise of mobile malware: How to protect your device from malicious software.
• Mobile phishing attacks: How to protect your device from being scammed.
• The dangers of public Wi-Fi: How to protect your device from being hacked.
• How to keep your data safe on your mobile device: Tips for keeping your personal information secure.

🕵Top 10 Cyber Security Topics

• Cybersecurity threats and attacks
• Cybersecurity risks and vulnerabilities
• Cybersecurity best practices
• Cybersecurity awareness and training
• Cybersecurity tools and technologies
• Cybersecurity policy and compliance
• Cybersecurity incident response
• Cybersecurity governance
• Cybersecurity risk management
• Cybersecurity strategy

👨‍💻Cyber Security Research Topics 2023

• The future of cyber security: what trends will shape the field in the coming years?
• The impact of AI and machine learning on cyber security
• The role of quantum computing in cyber security
• The challenges of securing the IoT
• The evolving threat landscape: what new threats are emerging and how can we defend against them?
• The role of data in cyber security: how can we better protect our data?
• The importance of user education in cyber security
• The challenges of securing mobile devices
• The future of cyber warfare: what trends are emerging?
• The role of cryptography in cyber security

🔎Best Cyber Security Research Topics

• The Impact of Cybersecurity on Businesses and Consumers
• The Evolution of Cybersecurity Threats and Attacks
• The Role of Cybersecurity in National Security
• The Economics of Cybersecurity
• The Psychology of Cybersecurity
• The Sociology of Cybersecurity
• The Ethics of Cybersecurity
• The History of Cybersecurity
• Cybersecurity threats and attacks.
• Cybersecurity policies and procedures.
• Cybersecurity awareness and training.
• Cybersecurity technologies and solutions.
• Cybersecurity risk management.
• Cybersecurity incident response.
• Cybersecurity governance.
• Cybersecurity compliance.
• Cybersecurity standards.
• Cybersecurity best practices.

👨‍🔬Cyber Security Future Research Topics

• Developing more effective methods for detecting and responding to cyber attacks
• Investigating the role of social media in cyber security
• Examining the impact of cloud computing on cyber security
• Investigating the security implications of the Internet of Things
• Studying the effectiveness of current cyber security measures
• Identifying new cyber security threats and vulnerabilities
• Developing more effective cyber security policies
• Examining the ethical implications of cyber security

📑Cyber Security Topics For Research Paper

• Cyber security threats and vulnerabilities.
• Cyber security incident response and management.
• Cyber security risk management.
• Cyber security awareness and training.
• Cyber security controls and countermeasures.
• Cyber security governance.
• Cyber security standards.
• Cyber security insurance.
• Cyber security and the law.
• The future of cyber security.

👩‍💻Cyber Security Topics on Computer and Software

• Cyber security risks associated with computer software
• The importance of keeping computer software up to date
• How to protect your computer from malware and other threats
• The best practices for securing your computer and software
• The different types of cyber security threats and how to avoid them
• The importance of cyber security awareness and education
• The role of cyber security in protecting critical infrastructure

Readers also enjoyed

WHY WAIT? PLACE AN ORDER RIGHT NOW!

Just fill out the form, press the button, and have no worries!

We use cookies to give you the best experience possible. By continuing we’ll assume you board with our cookie policy.

• Search by keyword
• Search by citation

Page 1 of 5

Polar code-based secure transmission with higher message rate combining channel entropy and computational entropy

The existing physical layer security schemes, which are based on the key generation model and the wire-tap channel model, achieve security by utilizing channel reciprocity entropy and noise entropy, respective...

• View Full Text

Dissecting zero trust: research landscape and its implementation in IoT

As a progressive security strategy, the zero trust model has attracted notable attention and importance within the realm of network security, especially in the context of the Internet of Things (IoT). This pap...

Study of smart grid cyber-security, examining architectures, communication networks, cyber-attacks, countermeasure techniques, and challenges

Smart Grid (SG) technology utilizes advanced network communication and monitoring technologies to manage and regulate electricity generation and transport. However, this increased reliance on technology and co...

A multi-agent adaptive deep learning framework for online intrusion detection

The network security analyzers use intrusion detection systems (IDSes) to distinguish malicious traffic from benign ones. The deep learning-based (DL-based) IDSes are proposed to auto-extract high-level featur...

Iterative and mixed-spaces image gradient inversion attack in federated learning

As a distributed learning paradigm, federated learning is supposed to protect data privacy without exchanging users’ local data. Even so, the gradient inversion attack , in which the adversary can reconstruct the ...

Winternitz stack protocols for embedded systems and IoT

This paper proposes and evaluates a new bipartite post-quantum digital signature protocol based on Winternitz chains and an  oracle. Mutually mistrustful Alice and Bob are able to agree and sign a series of do...

Joint contrastive learning and belief rule base for named entity recognition in cybersecurity

Named Entity Recognition (NER) in cybersecurity is crucial for mining information during cybersecurity incidents. Current methods rely on pre-trained models for rich semantic text embeddings, but the challenge...

DTA: distribution transform-based attack for query-limited scenario

In generating adversarial examples, the conventional black-box attack methods rely on sufficient feedback from the to-be-attacked models by repeatedly querying until the attack is successful, which usually res...

A survey on lattice-based digital signature

Lattice-based digital signature has become one of the widely recognized post-quantum algorithms because of its simple algebraic operation, rich mathematical foundation and worst-case security, and also an impo...

Shorter ZK-SNARKs from square span programs over ideal lattices

Zero-knowledge succinct non-interactive arguments of knowledge (zk-SNARKs) are cryptographic protocols that offer efficient and privacy-preserving means of verifying NP language relations and have drawn consid...

Revocable and verifiable weighted attribute-based encryption with collaborative access for electronic health record in cloud

The encryption of user data is crucial when employing electronic health record services to guarantee the security of the data stored on cloud servers. Attribute-based encryption (ABE) scheme is considered a po...

Maxwell’s Demon in MLP-Mixer: towards transferable adversarial attacks

Models based on MLP-Mixer architecture are becoming popular, but they still suffer from adversarial examples. Although it has been shown that MLP-Mixer is more robust to adversarial attacks compared to convolu...

Practical solutions in fully homomorphic encryption: a survey analyzing existing acceleration methods

Fully homomorphic encryption (FHE) has experienced significant development and continuous breakthroughs in theory, enabling its widespread application in various fields, like outsourcing computation and secure...

A circuit area optimization of MK-3 S-box

In MILCOM 2015, Kelly et al. proposed the authentication encryption algorithm MK-3, which applied the 16-bit S-box. This paper aims to implement the 16-bit S-box with less circuit area. First, we classified th...

Intrusion detection system for controller area network

The rapid expansion of intra-vehicle networks has increased the number of threats to such networks. Most modern vehicles implement various physical and data-link layer technologies. Vehicles are becoming incre...

CT-GCN+: a high-performance cryptocurrency transaction graph convolutional model for phishing node classification

Due to the anonymous and contract transfer nature of blockchain cryptocurrencies, they are susceptible to fraudulent incidents such as phishing. This poses a threat to the property security of users and hinder...

Enhanced detection of obfuscated malware in memory dumps: a machine learning approach for advanced cybersecurity

In the realm of cybersecurity, the detection and analysis of obfuscated malware remain a critical challenge, especially in the context of memory dumps. This research paper presents a novel machine learning-bas...

BRITD: behavior rhythm insider threat detection with time awareness and user adaptation

Researchers usually detect insider threats by analyzing user behavior. The time information of user behavior is an important concern in internal threat detection.

F3l: an automated and secure function-level low-overhead labeled encrypted traffic dataset construction method for IM in Android

Fine-grained function-level encrypted traffic classification is an essential approach to maintaining network security. Machine learning and deep learning have become mainstream methods to analyze traffic, and ...

WAS: improved white-box cryptographic algorithm over AS iteration

The attacker in white-box model has full access to software implementation of a cryptographic algorithm and full control over its execution environment. In order to solve the issues of high storage cost and in...

Full-round impossible differential attack on shadow block cipher

Lightweight block ciphers are the essential encryption algorithm for devices with limited resources. Its goal is to ensure the security of data transmission through resource-constrained devices. Impossible dif...

Minimizing CNOT-count in quantum circuit of the extended Shor’s algorithm for ECDLP

The elliptic curve discrete logarithm problem (ECDLP) is a popular choice for cryptosystems due to its high level of security. However, with the advent of the extended Shor’s algorithm, there is concern that E...

Towards the transferable audio adversarial attack via ensemble methods

In recent years, deep learning (DL) models have achieved significant progress in many domains, such as autonomous driving, facial recognition, and speech recognition. However, the vulnerability of deep learnin...

LayerCFL: an efficient federated learning with layer-wised clustering

Federated Learning (FL) suffers from the Non-IID problem in practice, which poses a challenge for efficient and accurate model training. To address this challenge, prior research has introduced clustered FL (C...

A novel botnet attack detection for IoT networks based on communication graphs

Intrusion detection systems have been proposed for the detection of botnet attacks. Various types of centralized or distributed cloud-based machine learning and deep learning models have been suggested. Howeve...

Machine learning based fileless malware traffic classification using image visualization

In today’s interconnected world, network traffic is replete with adversarial attacks. As technology evolves, these attacks are also becoming increasingly sophisticated, making them even harder to detect. Fortu...

Research on privacy information retrieval model based on hybrid homomorphic encryption

The computational complexity of privacy information retrieval protocols is often linearly related to database size. When the database size is large, the efficiency of privacy information retrieval protocols is...

Performance evaluation of Cuckoo filters as an enhancement tool for password cracking

Cyberthreats continue their expansion, becoming more and more complex and varied. However, credentials and passwords are still a critical point in security. Password cracking can be a powerful tool to fight ag...

Tor network anonymity evaluation based on node anonymity

In order to address the shortcomings of traditional anonymity network anonymity evaluation methods, which only analyze from the perspective of the overall network and ignore the attributes of individual nodes,...

Verifiable delay functions and delay encryptions from hyperelliptic curves

Verifiable delay functions (VDFs) and delay encryptions (DEs) are two important primitives in decentralized systems, while existing constructions are mainly based on time-lock puzzles. A disparate framework ha...

MSLFuzzer: black-box fuzzing of SOHO router devices via message segment list inference

The popularity of small office and home office routers has brought convenience, but it also caused many security issues due to vulnerabilities. Black-box fuzzing through network protocols to discover vulnerabi...

A deep learning aided differential distinguisher improvement framework with more lightweight and universality

In CRYPTO 2019, Gohr opens up a new direction for cryptanalysis. He successfully applied deep learning to differential cryptanalysis against the NSA block cipher SPECK32/64, achieving higher accuracy than trad...

Attack based on data: a novel perspective to attack sensitive points directly

Adversarial attack for time-series classification model is widely explored and many attack methods are proposed. But there is not a method of attack based on the data itself. In this paper, we innovatively pro...

Improved lower bound for the complexity of unique shortest vector problem

Unique shortest vector problem (uSVP) plays an important role in lattice based cryptography. Many cryptographic schemes based their security on it. For the cofidence of those applications, it is essential to c...

Evolution of blockchain consensus algorithms: a review on the latest milestones of blockchain consensus algorithms

Blockchain technology has gained widespread adoption in recent years due to its ability to enable secure and transparent record-keeping and data transfer. A critical aspect of blockchain technology is the use ...

Graph neural network based approach to automatically assigning common weakness enumeration identifiers for vulnerabilities

Vulnerability reports are essential for improving software security since they record key information on vulnerabilities. In a report, CWE denotes the weakness of the vulnerability and thus helps quickly under...

EPASAD: ellipsoid decision boundary based Process-Aware Stealthy Attack Detector

Due to the importance of Critical Infrastructure (CI) in a nation’s economy, they have been lucrative targets for cyber attackers. These critical infrastructures are usually Cyber-Physical Systems such as powe...

Generic attacks on small-state stream cipher constructions in the multi-user setting

Small-state stream ciphers (SSCs), which violate the principle that the state size should exceed the key size by a factor of two, still demonstrate robust security properties while maintaining a lightweight de...

Evicting and filling attack for linking multiple network addresses of Bitcoin nodes

Bitcoin is a decentralized P2P cryptocurrency. It supports users to use pseudonyms instead of network addresses to send and receive transactions at the data layer, hiding users’ real network identities. Tradit...

Aparecium: understanding and detecting scam behaviors on Ethereum via biased random walk

Ethereum’s high attention, rich business, certain anonymity, and untraceability have attracted a group of attackers. Cybercrime on it has become increasingly rampant, among which scam behavior is convenient, c...

An efficient permutation approach for SbPN-based symmetric block ciphers

It is challenging to devise lightweight cryptographic primitives efficient in both hardware and software that can provide an optimum level of security to diverse Internet of Things applications running on low-...

IHVFL: a privacy-enhanced intention-hiding vertical federated learning framework for medical data

Vertical Federated Learning (VFL) has many applications in the field of smart healthcare with excellent performance. However, current VFL systems usually primarily focus on the privacy protection during model ...

Intrusion detection systems for wireless sensor networks using computational intelligence techniques

Network Intrusion Detection Systems (NIDS) are utilized to find hostile network connections. This can be accomplished by looking at traffic network activity, but it takes a lot of work. The NIDS heavily utiliz...

Detecting fake reviewers in heterogeneous networks of buyers and sellers: a collaborative training-based spammer group algorithm

It is not uncommon for malicious sellers to collude with fake reviewers (also called spammers) to write fake reviews for multiple products to either demote competitors or promote their products’ reputations, f...

Continuously non-malleable codes from block ciphers in split-state model

Non-malleable code is an encoding scheme that is useful in situations where traditional error correction or detection is impossible to achieve. It ensures with high probability that decoded message is either c...

Use of subword tokenization for domain generation algorithm classification

Domain name generation algorithm (DGA) classification is an essential but challenging problem. Both feature-extracting machine learning (ML) methods and deep learning (DL) models such as convolutional neural n...

A buffer overflow detection and defense method based on RISC-V instruction set extension

Buffer overflow poses a serious threat to the memory security of modern operating systems. It overwrites the contents of other memory areas by breaking through the buffer capacity limit, destroys the system ex...

Quantized autoencoder (QAE) intrusion detection system for anomaly detection in resource-constrained IoT devices using RT-IoT2022 dataset

In recent years, many researchers focused on unsupervised learning for network anomaly detection in edge devices to identify attacks. The deployment of the unsupervised autoencoder model is computationally exp...

Detecting compromised email accounts via login behavior characterization

The illegal use of compromised email accounts by adversaries can have severe consequences for enterprises and society. Detecting compromised email accounts is more challenging than in the social network field,...

Security estimation of LWE via BKW algorithms

The Learning With Errors (LWE) problem is widely used in lattice-based cryptography, which is the most promising post-quantum cryptography direction. There are a variety of LWE-solving methods, which can be cl...

• Editorial Board
• Sign up for article alerts and news from this journal

Affiliated with

The Institute of Information Engineering (IIE) is a national research institute in Beijing that specializes in comprehensive research on theories and applications related to information technology.

IIE strives to be a leading global academic institution by creating first-class research platforms and attracting top researchers. It also seeks to become an important national strategic power in the field of information technology.

IIE’s mission is to promote China’s innovation and industrial competitiveness by advancing information science, standards, and technology in ways that enhance economic security and public safety as well as improve our quality of life.

Read more..

The journal is indexed by

• EI Compendex
• Emerging Sources Citation Index
• EBSCO Discovery Service
• Institute of Scientific and Technical Information of China
• Google Scholar
• Norwegian Register for Scientific Journals and Series
• OCLC WorldCat Discovery Service
• ProQuest-ExLibris Primo
• ProQuest-ExLibris Summon
• TD Net Discovery Service
• UGC-CARE List (India)

Annual Journal Metrics

2022 Citation Impact 3.1 - 2-year Impact Factor 4.8 - 5-year Impact Factor 2.071 - SNIP (Source Normalized Impact per Paper) 1.266 - SJR (SCImago Journal Rank)

2023 Speed 8 days submission to first editorial decision for all manuscripts (Median) 95 days submission to accept (Median)

2023 Usage  408,523 downloads 15 Altmetric mentions 

• ISSN: 2523-3246 (electronic)

Programs submenu

Regions submenu, topics submenu, poni 2024 capstone conference, dod's gaza pier and the maritime corridor—gaza: the human toll, lessons from myanmar.

• Abshire-Inamori Leadership Academy
• Aerospace Security Project
• Africa Program
• Americas Program
• Arleigh A. Burke Chair in Strategy
• Asia Maritime Transparency Initiative
• Asia Program
• Australia Chair
• Brzezinski Chair in Global Security and Geostrategy
• Brzezinski Institute on Geostrategy
• Chair in U.S.-India Policy Studies
• China Power Project
• Chinese Business and Economics
• Defending Democratic Institutions
• Defense-Industrial Initiatives Group
• Defense 360
• Defense Budget Analysis
• Diversity and Leadership in International Affairs Project
• Economics Program
• Emeritus Chair in Strategy
• Energy Security and Climate Change Program
• Europe, Russia, and Eurasia Program
• Freeman Chair in China Studies
• Futures Lab
• Geoeconomic Council of Advisers
• Global Food and Water Security Program
• Global Health Policy Center
• Hess Center for New Frontiers
• Human Rights Initiative
• Humanitarian Agenda
• Intelligence, National Security, and Technology Program

International Security Program

• Japan Chair
• Kissinger Chair
• Korea Chair
• Langone Chair in American Leadership
• Middle East Program
• Missile Defense Project
• Project on Critical Minerals Security
• Project on Fragility and Mobility
• Project on Nuclear Issues
• Project on Prosperity and Development
• Project on Trade and Technology
• Renewing American Innovation Project
• Scholl Chair in International Business
• Smart Women, Smart Power
• Southeast Asia Program
• Stephenson Ocean Security Project

Strategic Technologies Program

• Transnational Threats Project
• Wadhwani Center for AI and Advanced Technologies
• All Regions
• Australia, New Zealand & Pacific
• Middle East
• Russia and Eurasia
• American Innovation
• Civic Education
• Climate Change

Cybersecurity

• Defense Budget and Acquisition
• Defense and Security
• Energy and Sustainability
• Food Security
• Gender and International Security
• Geopolitics
• Global Health
• Human Rights
• Humanitarian Assistance
• Intelligence
• International Development
• Maritime Issues and Oceans
• Missile Defense
• Nuclear Issues
• Transnational Threats
• Water Security

Led by the Strategic Technologies Program and the International Security Program , CSIS’s cybersecurity portfolio covers cyber warfare, encryption, military cyber capacity, hacking, financial terrorism, and more.

Photo: iLab/CSIS

Space Threat Assessment 2024

The 2024 Space Threat Assessment covers the growing counterspace capabilities of China, Russia, India, Iran, North Korea, and others. It also features analysis on the normalization of deviance on orbit and a look into coalitions of convenience that are being formed. 

Report by Clayton Swope, Kari A. Bingen, Makena Young, Madeleine Chang, Stephanie Songer, and Jeremy Tammelleo — April 17, 2024

Eroding Trust in Government: What Games, Surveys, and Scenarios Reveal about Alternative Cyber Futures

Report by Yasir Atalan, Benjamin Jensen, and Jose M. Macias III — April 8, 2024

TikTok and National Security

Commentary by James Andrew Lewis — March 13, 2024

Government Use of Deepfakes

Report by Daniel Byman, Daniel W. Linna Jr., and V. S. Subrahmanian — March 12, 2024

Latest Podcasts

The UN Ad Hoc Cybercrime Negotiations: The End Is Nigh, Or Is It?

Podcast Episode by James Andrew Lewis and Christopher Painter — May 1, 2024

“Space Threat Assessment 2024”: Audio Brief with Clayton Swope

Podcast Episode by Clayton Swope — April 17, 2024

“Eroding Trust in Government: What Games, Surveys, and Scenarios Reveal about Alternative Cyber Futures”: Audio Brief with Yasir Atalan

Podcast Episode by Yasir Atalan — April 8, 2024

Venture Meets Mission with Arun Gupta

Podcast Episode by James Andrew Lewis — March 27, 2024

Past Events

The New Era of U.S.-Japan Strategic Cooperation: A Dialogue with Japanese Lawmakers

Cyber Incident Reporting in the Communications Sector

Counterspace Trends: An Evolving Global Landscape

Shaping the Future of Federal Cybersecurity: Insights from FCEBs

5G/6G Technology and the Future of Global Security

A Discussion of the 2023 Counter Ransomware Initiative with DNSA Anne Neuberger

CISA's Evolving .gov Mission: Report Rollout Event

Managing Geopolitical Risk in Mexico's ICT Sector

Related programs.

James Andrew Lewis

Suzanne Spaulding

Emily Harding

Clayton Swope

All cybersecurity content, type open filter submenu.

• Article (152)
• Event (143)
• Expert/Staff (32)
• Podcast Episode (82)
• Report (66)

Article Type open filter submenu

Report type open filter submenu, region open filter submenu.

• Afghanistan (5)
• Americas (39)
• Australia, New Zealand & Pacific (5)
• Caribbean Security (1)
• Central Asia (1)
• Eastern Europe (12)
• Europe (40)
• European Union (18)
• Middle East (10)
• North Africa (1)
• North America (59)
• Russia (34)
• Russia and Eurasia (29)
• South America (7)
• Southeast Asia (11)
• Sub-Saharan Africa (4)
• The South Caucasus (1)

The Mind of the CISO: Decoding the GenAI Impact

Join CSIS for a discussion on this latest report 'The Mind of the CISO: Decoding the GenAI Impact' that evaluates how Artificial Intelligence and GenAI is affecting the role of the CISO. 

Event — May 16, 2024

The Japan Chair welcomes leading Japanese lawmakers to CSIS to discuss near-term priorities for the U.S.-Japan alliance in the wake of the Biden-Kishida summit. 

Event — May 3, 2024

Join CSIS for a discussion of the launch of the Cyber Incident Reporting for Critical Infrastructure Act (CIRCIA) and how private sector efforts can strengthen incident awareness and response in the IT and communications sectors.

Event — May 1, 2024

In this episode, hosts Jim Lewis and Chris Painter engage in a dynamic conversation with return guest Ambassador (ret.) Deborah McCarthy. She shares insights, as the lead negotiator for the United States, on the status and prospects for the proposed United Nations Cybercrime Treaty.

Please join scholars from CSIS’s Aerospace Security Project and the Secure World Foundation as they discuss the latest counterspace weapons trends.

Event — April 17, 2024

A short, spoken-word summary from CSIS’s Clayton Swope on his report with Kari A. Bingen, Makena Young, Madeline Chang, Stephanie Songer, and Jeremy Tammelleo, Space Threat Assessment 2024.

In the future, malign actors will seek to undermine trust in government through disrupting basic needs and services such as food aid and medical assistance, in place of costly offensive cyber campaigns.

A short, spoken-word summary from CSIS’s Yasir Atalan on his report with Benjamin Jensen and Jose M. Macias III, Eroding Trust in Government: What Games, Surveys, and Scenarios Reveal about Alternative Cyber Futures. 

In the last episode of the podcast, host Jim Lewis talks to Arun Gupta, a venture capitalist, lecturer, entrepreneur and author of ‘ Venture Meets Mission’ . They discuss the landscape of venture capital and government collaboration, tech innovation and overcoming a risk-averse culture.

• Frontiers in Big Data
• Cybersecurity and Privacy
• Research Topics

Cybersecurity and Artificial Intelligence: Advances, Challenges, Opportunities, Threats

Total Downloads

Total Views and Downloads

About this Research Topic

Background: Cybersecurity and AI have become increasingly important in today's interconnected world. Developments in them and because of them find their way regularly not only to the scientific literature but to the media as well. Notwithstanding the benefits of AI, the increasing use of and ...

Keywords : Cybersecurity, Artificial Intelligence, Adversarial machine learning

Important Note : All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

Topic Editors

Topic coordinators, recent articles, submission deadlines, participating journals.

Manuscripts can be submitted to this Research Topic via the following journals:

total views

• Demographics

No records found

total views article views downloads topic views

Top countries

Top referring sites, about frontiers research topics.

With their unique mixes of varied contributions from Original Research to Review Articles, Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author.

• Search Menu
• Editor's Choice
• Author Guidelines
• Submission Site
• Open Access
• About Journal of Cybersecurity
• Editorial Board
• Advertising and Corporate Services
• Journals Career Network
• Self-Archiving Policy
• Journals on Oxford Academic
• Books on Oxford Academic

High-Impact Research from Journal of Cybersecurity

Explore a collection of the most read and most cited articles making an impact in the Journal of Cybersecurity  published within the past two years. This collection will be continuously updated with the journal's leading articles so be sure to revisit periodically to see what is being read and cited.

Also discover the articles being discussed the most on digital media by  exploring this Altmetric report  pulling the most discussed articles from the past year.

Recognizing and Celebrating Women in Science

Oxford University Press is proud to support diverse voices across our publishing. In this collection, we shine a spotlight on the representation of women in scientific fields, the gains that have been made in their fields, from research and major discoveries to advocacy and outreach, and amplify the voices of women who have made a career in scientific research.

Delve into the Women in Science collection

Affiliations

• Online ISSN 2057-2093
• Print ISSN 2057-2085
• Copyright © 2024 Oxford University Press
• About Oxford Academic
• Publish journals with us
• University press partners
• What we publish
• New features  
• Open access
• Institutional account management
• Rights and permissions
• Get help with access
• Accessibility
• Advertising
• Media enquiries
• Oxford University Press
• Oxford Languages
• University of Oxford

Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide

• Copyright © 2024 Oxford University Press
• Cookie settings
• Cookie policy
• Privacy policy
• Legal notice

This Feature Is Available To Subscribers Only

Sign In or Create an Account

This PDF is available to Subscribers Only

For full access to this pdf, sign in to an existing account, or purchase an annual subscription.

Cyber risk and cybersecurity: a systematic review of data availability

• Open access
• Published: 17 February 2022
• Volume 47 , pages 698–736, ( 2022 )

Cite this article

You have full access to this open access article

• Frank Cremer 1 ,
• Barry Sheehan   ORCID: orcid.org/0000-0003-4592-7558 1 ,
• Michael Fortmann 2 ,
• Arash N. Kia 1 ,
• Martin Mullins 1 ,
• Finbarr Murphy 1 &
• Stefan Materne 2  

65k Accesses

63 Citations

42 Altmetric

Explore all metrics

Cybercrime is estimated to have cost the global economy just under USD 1 trillion in 2020, indicating an increase of more than 50% since 2018. With the average cyber insurance claim rising from USD 145,000 in 2019 to USD 359,000 in 2020, there is a growing necessity for better cyber information sources, standardised databases, mandatory reporting and public awareness. This research analyses the extant academic and industry literature on cybersecurity and cyber risk management with a particular focus on data availability. From a preliminary search resulting in 5219 cyber peer-reviewed studies, the application of the systematic methodology resulted in 79 unique datasets. We posit that the lack of available data on cyber risk poses a serious problem for stakeholders seeking to tackle this issue. In particular, we identify a lacuna in open databases that undermine collective endeavours to better manage this set of risks. The resulting data evaluation and categorisation will support cybersecurity researchers and the insurance industry in their efforts to comprehend, metricise and manage cyber risks.

Similar content being viewed by others

Systematic Review: Cybersecurity Risk Taxonomy

A Survey of Cybersecurity Risk Management Frameworks

Cybersecurity Risk Management Frameworks in the Oil and Gas Sector: A Systematic Literature Review

Avoid common mistakes on your manuscript.

Introduction

Globalisation, digitalisation and smart technologies have escalated the propensity and severity of cybercrime. Whilst it is an emerging field of research and industry, the importance of robust cybersecurity defence systems has been highlighted at the corporate, national and supranational levels. The impacts of inadequate cybersecurity are estimated to have cost the global economy USD 945 billion in 2020 (Maleks Smith et al. 2020 ). Cyber vulnerabilities pose significant corporate risks, including business interruption, breach of privacy and financial losses (Sheehan et al. 2019 ). Despite the increasing relevance for the international economy, the availability of data on cyber risks remains limited. The reasons for this are many. Firstly, it is an emerging and evolving risk; therefore, historical data sources are limited (Biener et al. 2015 ). It could also be due to the fact that, in general, institutions that have been hacked do not publish the incidents (Eling and Schnell 2016 ). The lack of data poses challenges for many areas, such as research, risk management and cybersecurity (Falco et al. 2019 ). The importance of this topic is demonstrated by the announcement of the European Council in April 2021 that a centre of excellence for cybersecurity will be established to pool investments in research, technology and industrial development. The goal of this centre is to increase the security of the internet and other critical network and information systems (European Council 2021 ).

This research takes a risk management perspective, focusing on cyber risk and considering the role of cybersecurity and cyber insurance in risk mitigation and risk transfer. The study reviews the existing literature and open data sources related to cybersecurity and cyber risk. This is the first systematic review of data availability in the general context of cyber risk and cybersecurity. By identifying and critically analysing the available datasets, this paper supports the research community by aggregating, summarising and categorising all available open datasets. In addition, further information on datasets is attached to provide deeper insights and support stakeholders engaged in cyber risk control and cybersecurity. Finally, this research paper highlights the need for open access to cyber-specific data, without price or permission barriers.

The identified open data can support cyber insurers in their efforts on sustainable product development. To date, traditional risk assessment methods have been untenable for insurance companies due to the absence of historical claims data (Sheehan et al. 2021 ). These high levels of uncertainty mean that cyber insurers are more inclined to overprice cyber risk cover (Kshetri 2018 ). Combining external data with insurance portfolio data therefore seems to be essential to improve the evaluation of the risk and thus lead to risk-adjusted pricing (Bessy-Roland et al. 2021 ). This argument is also supported by the fact that some re/insurers reported that they are working to improve their cyber pricing models (e.g. by creating or purchasing databases from external providers) (EIOPA 2018 ). Figure  1 provides an overview of pricing tools and factors considered in the estimation of cyber insurance based on the findings of EIOPA ( 2018 ) and the research of Romanosky et al. ( 2019 ). The term cyber risk refers to all cyber risks and their potential impact.

An overview of the current cyber insurance informational and methodological landscape, adapted from EIOPA ( 2018 ) and Romanosky et al. ( 2019 )

Besides the advantage of risk-adjusted pricing, the availability of open datasets helps companies benchmark their internal cyber posture and cybersecurity measures. The research can also help to improve risk awareness and corporate behaviour. Many companies still underestimate their cyber risk (Leong and Chen 2020 ). For policymakers, this research offers starting points for a comprehensive recording of cyber risks. Although in many countries, companies are obliged to report data breaches to the respective supervisory authority, this information is usually not accessible to the research community. Furthermore, the economic impact of these breaches is usually unclear.

As well as the cyber risk management community, this research also supports cybersecurity stakeholders. Researchers are provided with an up-to-date, peer-reviewed literature of available datasets showing where these datasets have been used. For example, this includes datasets that have been used to evaluate the effectiveness of countermeasures in simulated cyberattacks or to test intrusion detection systems. This reduces a time-consuming search for suitable datasets and ensures a comprehensive review of those available. Through the dataset descriptions, researchers and industry stakeholders can compare and select the most suitable datasets for their purposes. In addition, it is possible to combine the datasets from one source in the context of cybersecurity or cyber risk. This supports efficient and timely progress in cyber risk research and is beneficial given the dynamic nature of cyber risks.

Cyber risks are defined as “operational risks to information and technology assets that have consequences affecting the confidentiality, availability, and/or integrity of information or information systems” (Cebula et al. 2014 ). Prominent cyber risk events include data breaches and cyberattacks (Agrafiotis et al. 2018 ). The increasing exposure and potential impact of cyber risk have been highlighted in recent industry reports (e.g. Allianz 2021 ; World Economic Forum 2020 ). Cyberattacks on critical infrastructures are ranked 5th in the World Economic Forum's Global Risk Report. Ransomware, malware and distributed denial-of-service (DDoS) are examples of the evolving modes of a cyberattack. One example is the ransomware attack on the Colonial Pipeline, which shut down the 5500 mile pipeline system that delivers 2.5 million barrels of fuel per day and critical liquid fuel infrastructure from oil refineries to states along the U.S. East Coast (Brower and McCormick 2021 ). These and other cyber incidents have led the U.S. to strengthen its cybersecurity and introduce, among other things, a public body to analyse major cyber incidents and make recommendations to prevent a recurrence (Murphey 2021a ). Another example of the scope of cyberattacks is the ransomware NotPetya in 2017. The damage amounted to USD 10 billion, as the ransomware exploited a vulnerability in the windows system, allowing it to spread independently worldwide in the network (GAO 2021 ). In the same year, the ransomware WannaCry was launched by cybercriminals. The cyberattack on Windows software took user data hostage in exchange for Bitcoin cryptocurrency (Smart 2018 ). The victims included the National Health Service in Great Britain. As a result, ambulances were redirected to other hospitals because of information technology (IT) systems failing, leaving people in need of urgent assistance waiting. It has been estimated that 19,000 cancelled treatment appointments resulted from losses of GBP 92 million (Field 2018 ). Throughout the COVID-19 pandemic, ransomware attacks increased significantly, as working from home arrangements increased vulnerability (Murphey 2021b ).

Besides cyberattacks, data breaches can also cause high costs. Under the General Data Protection Regulation (GDPR), companies are obliged to protect personal data and safeguard the data protection rights of all individuals in the EU area. The GDPR allows data protection authorities in each country to impose sanctions and fines on organisations they find in breach. “For data breaches, the maximum fine can be €20 million or 4% of global turnover, whichever is higher” (GDPR.EU 2021 ). Data breaches often involve a large amount of sensitive data that has been accessed, unauthorised, by external parties, and are therefore considered important for information security due to their far-reaching impact (Goode et al. 2017 ). A data breach is defined as a “security incident in which sensitive, protected, or confidential data are copied, transmitted, viewed, stolen, or used by an unauthorized individual” (Freeha et al. 2021 ). Depending on the amount of data, the extent of the damage caused by a data breach can be significant, with the average cost being USD 392 million Footnote 1 (IBM Security 2020 ).

This research paper reviews the existing literature and open data sources related to cybersecurity and cyber risk, focusing on the datasets used to improve academic understanding and advance the current state-of-the-art in cybersecurity. Furthermore, important information about the available datasets is presented (e.g. use cases), and a plea is made for open data and the standardisation of cyber risk data for academic comparability and replication. The remainder of the paper is structured as follows. The next section describes the related work regarding cybersecurity and cyber risks. The third section outlines the review method used in this work and the process. The fourth section details the results of the identified literature. Further discussion is presented in the penultimate section and the final section concludes.

Related work

Due to the significance of cyber risks, several literature reviews have been conducted in this field. Eling ( 2020 ) reviewed the existing academic literature on the topic of cyber risk and cyber insurance from an economic perspective. A total of 217 papers with the term ‘cyber risk’ were identified and classified in different categories. As a result, open research questions are identified, showing that research on cyber risks is still in its infancy because of their dynamic and emerging nature. Furthermore, the author highlights that particular focus should be placed on the exchange of information between public and private actors. An improved information flow could help to measure the risk more accurately and thus make cyber risks more insurable and help risk managers to determine the right level of cyber risk for their company. In the context of cyber insurance data, Romanosky et al. ( 2019 ) analysed the underwriting process for cyber insurance and revealed how cyber insurers understand and assess cyber risks. For this research, they examined 235 American cyber insurance policies that were publicly available and looked at three components (coverage, application questionnaires and pricing). The authors state in their findings that many of the insurers used very simple, flat-rate pricing (based on a single calculation of expected loss), while others used more parameters such as the asset value of the company (or company revenue) or standard insurance metrics (e.g. deductible, limits), and the industry in the calculation. This is in keeping with Eling ( 2020 ), who states that an increased amount of data could help to make cyber risk more accurately measured and thus more insurable. Similar research on cyber insurance and data was conducted by Nurse et al. ( 2020 ). The authors examined cyber insurance practitioners' perceptions and the challenges they face in collecting and using data. In addition, gaps were identified during the research where further data is needed. The authors concluded that cyber insurance is still in its infancy, and there are still several unanswered questions (for example, cyber valuation, risk calculation and recovery). They also pointed out that a better understanding of data collection and use in cyber insurance would be invaluable for future research and practice. Bessy-Roland et al. ( 2021 ) come to a similar conclusion. They proposed a multivariate Hawkes framework to model and predict the frequency of cyberattacks. They used a public dataset with characteristics of data breaches affecting the U.S. industry. In the conclusion, the authors make the argument that an insurer has a better knowledge of cyber losses, but that it is based on a small dataset and therefore combination with external data sources seems essential to improve the assessment of cyber risks.

Several systematic reviews have been published in the area of cybersecurity (Kruse et al. 2017 ; Lee et al. 2020 ; Loukas et al. 2013 ; Ulven and Wangen 2021 ). In these papers, the authors concentrated on a specific area or sector in the context of cybersecurity. This paper adds to this extant literature by focusing on data availability and its importance to risk management and insurance stakeholders. With a priority on healthcare and cybersecurity, Kruse et al. ( 2017 ) conducted a systematic literature review. The authors identified 472 articles with the keywords ‘cybersecurity and healthcare’ or ‘ransomware’ in the databases Cumulative Index of Nursing and Allied Health Literature, PubMed and Proquest. Articles were eligible for this review if they satisfied three criteria: (1) they were published between 2006 and 2016, (2) the full-text version of the article was available, and (3) the publication is a peer-reviewed or scholarly journal. The authors found that technological development and federal policies (in the U.S.) are the main factors exposing the health sector to cyber risks. Loukas et al. ( 2013 ) conducted a review with a focus on cyber risks and cybersecurity in emergency management. The authors provided an overview of cyber risks in communication, sensor, information management and vehicle technologies used in emergency management and showed areas for which there is still no solution in the literature. Similarly, Ulven and Wangen ( 2021 ) reviewed the literature on cybersecurity risks in higher education institutions. For the literature review, the authors used the keywords ‘cyber’, ‘information threats’ or ‘vulnerability’ in connection with the terms ‘higher education, ‘university’ or ‘academia’. A similar literature review with a focus on Internet of Things (IoT) cybersecurity was conducted by Lee et al. ( 2020 ). The review revealed that qualitative approaches focus on high-level frameworks, and quantitative approaches to cybersecurity risk management focus on risk assessment and quantification of cyberattacks and impacts. In addition, the findings presented a four-step IoT cyber risk management framework that identifies, quantifies and prioritises cyber risks.

Datasets are an essential part of cybersecurity research, underlined by the following works. Ilhan Firat et al. ( 2021 ) examined various cybersecurity datasets in detail. The study was motivated by the fact that with the proliferation of the internet and smart technologies, the mode of cyberattacks is also evolving. However, in order to prevent such attacks, they must first be detected; the dissemination and further development of cybersecurity datasets is therefore critical. In their work, the authors observed studies of datasets used in intrusion detection systems. Khraisat et al. ( 2019 ) also identified a need for new datasets in the context of cybersecurity. The researchers presented a taxonomy of current intrusion detection systems, a comprehensive review of notable recent work, and an overview of the datasets commonly used for assessment purposes. In their conclusion, the authors noted that new datasets are needed because most machine-learning techniques are trained and evaluated on the knowledge of old datasets. These datasets do not contain new and comprehensive information and are partly derived from datasets from 1999. The authors noted that the core of this issue is the availability of new public datasets as well as their quality. The availability of data, how it is used, created and shared was also investigated by Zheng et al. ( 2018 ). The researchers analysed 965 cybersecurity research papers published between 2012 and 2016. They created a taxonomy of the types of data that are created and shared and then analysed the data collected via datasets. The researchers concluded that while datasets are recognised as valuable for cybersecurity research, the proportion of publicly available datasets is limited.

The main contributions of this review and what differentiates it from previous studies can be summarised as follows. First, as far as we can tell, it is the first work to summarise all available datasets on cyber risk and cybersecurity in the context of a systematic review and present them to the scientific community and cyber insurance and cybersecurity stakeholders. Second, we investigated, analysed, and made available the datasets to support efficient and timely progress in cyber risk research. And third, we enable comparability of datasets so that the appropriate dataset can be selected depending on the research area.

Methodology

Process and eligibility criteria.

The structure of this systematic review is inspired by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework (Page et al. 2021 ), and the search was conducted from 3 to 10 May 2021. Due to the continuous development of cyber risks and their countermeasures, only articles published in the last 10 years were considered. In addition, only articles published in peer-reviewed journals written in English were included. As a final criterion, only articles that make use of one or more cybersecurity or cyber risk datasets met the inclusion criteria. Specifically, these studies presented new or existing datasets, used them for methods, or used them to verify new results, as well as analysed them in an economic context and pointed out their effects. The criterion was fulfilled if it was clearly stated in the abstract that one or more datasets were used. A detailed explanation of this selection criterion can be found in the ‘Study selection’ section.

Information sources

In order to cover a complete spectrum of literature, various databases were queried to collect relevant literature on the topic of cybersecurity and cyber risks. Due to the spread of related articles across multiple databases, the literature search was limited to the following four databases for simplicity: IEEE Xplore, Scopus, SpringerLink and Web of Science. This is similar to other literature reviews addressing cyber risks or cybersecurity, including Sardi et al. ( 2021 ), Franke and Brynielsson ( 2014 ), Lagerström (2019), Eling and Schnell ( 2016 ) and Eling ( 2020 ). In this paper, all databases used in the aforementioned works were considered. However, only two studies also used all the databases listed. The IEEE Xplore database contains electrical engineering, computer science, and electronics work from over 200 journals and three million conference papers (IEEE 2021 ). Scopus includes 23,400 peer-reviewed journals from more than 5000 international publishers in the areas of science, engineering, medicine, social sciences and humanities (Scopus 2021 ). SpringerLink contains 3742 journals and indexes over 10 million scientific documents (SpringerLink 2021 ). Finally, Web of Science indexes over 9200 journals in different scientific disciplines (Science 2021 ).

A search string was created and applied to all databases. To make the search efficient and reproducible, the following search string with Boolean operator was used in all databases: cybersecurity OR cyber risk AND dataset OR database. To ensure uniformity of the search across all databases, some adjustments had to be made for the respective search engines. In Scopus, for example, the Advanced Search was used, and the field code ‘Title-ABS-KEY’ was integrated into the search string. For IEEE Xplore, the search was carried out with the Search String in the Command Search and ‘All Metadata’. In the Web of Science database, the Advanced Search was used. The special feature of this search was that it had to be carried out in individual steps. The first search was carried out with the terms cybersecurity OR cyber risk with the field tag Topic (T.S. =) and the second search with dataset OR database. Subsequently, these searches were combined, which then delivered the searched articles for review. For SpringerLink, the search string was used in the Advanced Search under the category ‘Find the resources with all of the words’. After conducting this search string, 5219 studies could be found. According to the eligibility criteria (period, language and only scientific journals), 1581 studies were identified in the databases:

Scopus: 135

Springer Link: 548

Web of Science: 534

An overview of the process is given in Fig.  2 . Combined with the results from the four databases, 854 articles without duplicates were identified.

Literature search process and categorisation of the studies

Study selection

In the final step of the selection process, the articles were screened for relevance. Due to a large number of results, the abstracts were analysed in the first step of the process. The aim was to determine whether the article was relevant for the systematic review. An article fulfilled the criterion if it was recognisable in the abstract that it had made a contribution to datasets or databases with regard to cyber risks or cybersecurity. Specifically, the criterion was considered to be met if the abstract used datasets that address the causes or impacts of cyber risks, and measures in the area of cybersecurity. In this process, the number of articles was reduced to 288. The articles were then read in their entirety, and an expert panel of six people decided whether they should be used. This led to a final number of 255 articles. The years in which the articles were published and the exact number can be seen in Fig.  3 .

Distribution of studies

Data collection process and synthesis of the results

For the data collection process, various data were extracted from the studies, including the names of the respective creators, the name of the dataset or database and the corresponding reference. It was also determined where the data came from. In the context of accessibility, it was determined whether access is free, controlled, available for purchase or not available. It was also determined when the datasets were created and the time period referenced. The application type and domain characteristics of the datasets were identified.

This section analyses the results of the systematic literature review. The previously identified studies are divided into three categories: datasets on the causes of cyber risks, datasets on the effects of cyber risks and datasets on cybersecurity. The classification is based on the intended use of the studies. This system of classification makes it easier for stakeholders to find the appropriate datasets. The categories are evaluated individually. Although complete information is available for a large proportion of datasets, this is not true for all of them. Accordingly, the abbreviation N/A has been inserted in the respective characters to indicate that this information could not be determined by the time of submission. The term ‘use cases in the literature’ in the following and supplementary tables refers to the application areas in which the corresponding datasets were used in the literature. The areas listed there refer to the topic area on which the researchers conducted their research. Since some datasets were used interdisciplinarily, the listed use cases in the literature are correspondingly longer. Before discussing each category in the next sections, Fig.  4 provides an overview of the number of datasets found and their year of creation. Figure  5 then shows the relationship between studies and datasets in the period under consideration. Figure  6 shows the distribution of studies, their use of datasets and their creation date. The number of datasets used is higher than the number of studies because the studies often used several datasets (Table 1 ).

Distribution of dataset results

Correlation between the studies and the datasets

Distribution of studies and their use of datasets

Most of the datasets are generated in the U.S. (up to 58.2%). Canada and Australia rank next, with 11.3% and 5% of all the reviewed datasets, respectively.

Additionally, to create value for the datasets for the cyber insurance industry, an assessment of the applicability of each dataset has been provided for cyber insurers. This ‘Use Case Assessment’ includes the use of the data in the context of different analyses, calculation of cyber insurance premiums, and use of the information for the design of cyber insurance contracts or for additional customer services. To reasonably account for the transition of direct hyperlinks in the future, references were directed to the main websites for longevity (nearest resource point). In addition, the links to the main pages contain further information on the datasets and different versions related to the operating systems. The references were chosen in such a way that practitioners get the best overview of the respective datasets.

Case datasets

This section presents selected articles that use the datasets to analyse the causes of cyber risks. The datasets help identify emerging trends and allow pattern discovery in cyber risks. This information gives cybersecurity experts and cyber insurers the data to make better predictions and take appropriate action. For example, if certain vulnerabilities are not adequately protected, cyber insurers will demand a risk surcharge leading to an improvement in the risk-adjusted premium. Due to the capricious nature of cyber risks, existing data must be supplemented with new data sources (for example, new events, new methods or security vulnerabilities) to determine prevailing cyber exposure. The datasets of cyber risk causes could be combined with existing portfolio data from cyber insurers and integrated into existing pricing tools and factors to improve the valuation of cyber risks.

A portion of these datasets consists of several taxonomies and classifications of cyber risks. Aassal et al. ( 2020 ) propose a new taxonomy of phishing characteristics based on the interpretation and purpose of each characteristic. In comparison, Hindy et al. ( 2020 ) presented a taxonomy of network threats and the impact of current datasets on intrusion detection systems. A similar taxonomy was suggested by Kiwia et al. ( 2018 ). The authors presented a cyber kill chain-based taxonomy of banking Trojans features. The taxonomy built on a real-world dataset of 127 banking Trojans collected from December 2014 to January 2016 by a major U.K.-based financial organisation.

In the context of classification, Aamir et al. ( 2021 ) showed the benefits of machine learning for classifying port scans and DDoS attacks in a mixture of normal and attack traffic. Guo et al. ( 2020 ) presented a new method to improve malware classification based on entropy sequence features. The evaluation of this new method was conducted on different malware datasets.

To reconstruct attack scenarios and draw conclusions based on the evidence in the alert stream, Barzegar and Shajari ( 2018 ) use the DARPA2000 and MACCDC 2012 dataset for their research. Giudici and Raffinetti ( 2020 ) proposed a rank-based statistical model aimed at predicting the severity levels of cyber risk. The model used cyber risk data from the University of Milan. In contrast to the previous datasets, Skrjanc et al. ( 2018 ) used the older dataset KDD99 to monitor large-scale cyberattacks using a cauchy clustering method.

Amin et al. ( 2021 ) used a cyberattack dataset from the Canadian Institute for Cybersecurity to identify spatial clusters of countries with high rates of cyberattacks. In the context of cybercrime, Junger et al. ( 2020 ) examined crime scripts, key characteristics of the target company and the relationship between criminal effort and financial benefit. For their study, the authors analysed 300 cases of fraudulent activities against Dutch companies. With a similar focus on cybercrime, Mireles et al. ( 2019 ) proposed a metric framework to measure the effectiveness of the dynamic evolution of cyberattacks and defensive measures. To validate its usefulness, they used the DEFCON dataset.

Due to the rapidly changing nature of cyber risks, it is often impossible to obtain all information on them. Kim and Kim ( 2019 ) proposed an automated dataset generation system called CTIMiner that collects threat data from publicly available security reports and malware repositories. They released a dataset to the public containing about 640,000 records from 612 security reports published between January 2008 and 2019. A similar approach is proposed by Kim et al. ( 2020 ), using a named entity recognition system to extract core information from cyber threat reports automatically. They created a 498,000-tag dataset during their research (Ulven and Wangen 2021 ).

Within the framework of vulnerabilities and cybersecurity issues, Ulven and Wangen ( 2021 ) proposed an overview of mission-critical assets and everyday threat events, suggested a generic threat model, and summarised common cybersecurity vulnerabilities. With a focus on hospitality, Chen and Fiscus ( 2018 ) proposed several issues related to cybersecurity in this sector. They analysed 76 security incidents from the Privacy Rights Clearinghouse database. Supplementary Table 1 lists all findings that belong to the cyber causes dataset.

Impact datasets

This section outlines selected findings of the cyber impact dataset. For cyber insurers, these datasets can form an important basis for information, as they can be used to calculate cyber insurance premiums, evaluate specific cyber risks, formulate inclusions and exclusions in cyber wordings, and re-evaluate as well as supplement the data collected so far on cyber risks. For example, information on financial losses can help to better assess the loss potential of cyber risks. Furthermore, the datasets can provide insight into the frequency of occurrence of these cyber risks. The new datasets can be used to close any data gaps that were previously based on very approximate estimates or to find new results.

Eight studies addressed the costs of data breaches. For instance, Eling and Jung ( 2018 ) reviewed 3327 data breach events from 2005 to 2016 and identified an asymmetric dependence of monthly losses by breach type and industry. The authors used datasets from the Privacy Rights Clearinghouse for analysis. The Privacy Rights Clearinghouse datasets and the Breach level index database were also used by De Giovanni et al. ( 2020 ) to describe relationships between data breaches and bitcoin-related variables using the cointegration methodology. The data were obtained from the Department of Health and Human Services of healthcare facilities reporting data breaches and a national database of technical and organisational infrastructure information. Also in the context of data breaches, Algarni et al. ( 2021 ) developed a comprehensive, formal model that estimates the two components of security risks: breach cost and the likelihood of a data breach within 12 months. For their survey, the authors used two industrial reports from the Ponemon institute and VERIZON. To illustrate the scope of data breaches, Neto et al. ( 2021 ) identified 430 major data breach incidents among more than 10,000 incidents. The database created is available and covers the period 2018 to 2019.

With a direct focus on insurance, Biener et al. ( 2015 ) analysed 994 cyber loss cases from an operational risk database and investigated the insurability of cyber risks based on predefined criteria. For their study, they used data from the company SAS OpRisk Global Data. Similarly, Eling and Wirfs ( 2019 ) looked at a wide range of cyber risk events and actual cost data using the same database. They identified cyber losses and analysed them using methods from statistics and actuarial science. Using a similar reference, Farkas et al. ( 2021 ) proposed a method for analysing cyber claims based on regression trees to identify criteria for classifying and evaluating claims. Similar to Chen and Fiscus ( 2018 ), the dataset used was the Privacy Rights Clearinghouse database. Within the framework of reinsurance, Moro ( 2020 ) analysed cyber index-based information technology activity to see if index-parametric reinsurance coverage could suggest its cedant using data from a Symantec dataset.

Paté-Cornell et al. ( 2018 ) presented a general probabilistic risk analysis framework for cybersecurity in an organisation to be specified. The results are distributions of losses to cyberattacks, with and without considered countermeasures in support of risk management decisions based both on past data and anticipated incidents. The data used were from The Common Vulnerability and Exposures database and via confidential access to a database of cyberattacks on a large, U.S.-based organisation. A different conceptual framework for cyber risk classification and assessment was proposed by Sheehan et al. ( 2021 ). This framework showed the importance of proactive and reactive barriers in reducing companies’ exposure to cyber risk and quantifying the risk. Another approach to cyber risk assessment and mitigation was proposed by Mukhopadhyay et al. ( 2019 ). They estimated the probability of an attack using generalised linear models, predicted the security technology required to reduce the probability of cyberattacks, and used gamma and exponential distributions to best approximate the average loss data for each malicious attack. They also calculated the expected loss due to cyberattacks, calculated the net premium that would need to be charged by a cyber insurer, and suggested cyber insurance as a strategy to minimise losses. They used the CSI-FBI survey (1997–2010) to conduct their research.

In order to highlight the lack of data on cyber risks, Eling ( 2020 ) conducted a literature review in the areas of cyber risk and cyber insurance. Available information on the frequency, severity, and dependency structure of cyber risks was filtered out. In addition, open questions for future cyber risk research were set up. Another example of data collection on the impact of cyberattacks is provided by Sornette et al. ( 2013 ), who use a database of newspaper articles, press reports and other media to provide a predictive method to identify triggering events and potential accident scenarios and estimate their severity and frequency. A similar approach to data collection was used by Arcuri et al. ( 2020 ) to gather an original sample of global cyberattacks from newspaper reports sourced from the LexisNexis database. This collection is also used and applied to the fields of dynamic communication and cyber risk perception by Fang et al. ( 2021 ). To create a dataset of cyber incidents and disputes, Valeriano and Maness ( 2014 ) collected information on cyber interactions between rival states.

To assess trends and the scale of economic cybercrime, Levi ( 2017 ) examined datasets from different countries and their impact on crime policy. Pooser et al. ( 2018 ) investigated the trend in cyber risk identification from 2006 to 2015 and company characteristics related to cyber risk perception. The authors used a dataset of various reports from cyber insurers for their study. Walker-Roberts et al. ( 2020 ) investigated the spectrum of risk of a cybersecurity incident taking place in the cyber-physical-enabled world using the VERIS Community Database. The datasets of impacts identified are presented below. Due to overlap, some may also appear in the causes dataset (Supplementary Table 2).

Cybersecurity datasets

General intrusion detection.

General intrusion detection systems account for the largest share of countermeasure datasets. For companies or researchers focused on cybersecurity, the datasets can be used to test their own countermeasures or obtain information about potential vulnerabilities. For example, Al-Omari et al. ( 2021 ) proposed an intelligent intrusion detection model for predicting and detecting attacks in cyberspace, which was applied to dataset UNSW-NB 15. A similar approach was taken by Choras and Kozik ( 2015 ), who used machine learning to detect cyberattacks on web applications. To evaluate their method, they used the HTTP dataset CSIC 2010. For the identification of unknown attacks on web servers, Kamarudin et al. ( 2017 ) proposed an anomaly-based intrusion detection system using an ensemble classification approach. Ganeshan and Rodrigues ( 2020 ) showed an intrusion detection system approach, which clusters the database into several groups and detects the presence of intrusion in the clusters. In comparison, AlKadi et al. ( 2019 ) used a localisation-based model to discover abnormal patterns in network traffic. Hybrid models have been recommended by Bhattacharya et al. ( 2020 ) and Agrawal et al. ( 2019 ); the former is a machine-learning model based on principal component analysis for the classification of intrusion detection system datasets, while the latter is a hybrid ensemble intrusion detection system for anomaly detection using different datasets to detect patterns in network traffic that deviate from normal behaviour.

Agarwal et al. ( 2021 ) used three different machine learning algorithms in their research to find the most suitable for efficiently identifying patterns of suspicious network activity. The UNSW-NB15 dataset was used for this purpose. Kasongo and Sun ( 2020 ), Feed-Forward Deep Neural Network (FFDNN), Keshk et al. ( 2021 ), the privacy-preserving anomaly detection framework, and others also use the UNSW-NB 15 dataset as part of intrusion detection systems. The same dataset and others were used by Binbusayyis and Vaiyapuri ( 2019 ) to identify and compare key features for cyber intrusion detection. Atefinia and Ahmadi ( 2021 ) proposed a deep neural network model to reduce the false positive rate of an anomaly-based intrusion detection system. Fossaceca et al. ( 2015 ) focused in their research on the development of a framework that combined the outputs of multiple learners in order to improve the efficacy of network intrusion, and Gauthama Raman et al. ( 2020 ) presented a search algorithm based on Support Vector machine to improve the performance of the detection and false alarm rate to improve intrusion detection techniques. Ahmad and Alsemmeari ( 2020 ) targeted extreme learning machine techniques due to their good capabilities in classification problems and handling huge data. They used the NSL-KDD dataset as a benchmark.

With reference to prediction, Bakdash et al. ( 2018 ) used datasets from the U.S. Department of Defence to predict cyberattacks by malware. This dataset consists of weekly counts of cyber events over approximately seven years. Another prediction method was presented by Fan et al. ( 2018 ), which showed an improved integrated cybersecurity prediction method based on spatial-time analysis. Also, with reference to prediction, Ashtiani and Azgomi ( 2014 ) proposed a framework for the distributed simulation of cyberattacks based on high-level architecture. Kirubavathi and Anitha ( 2016 ) recommended an approach to detect botnets, irrespective of their structures, based on network traffic flow behaviour analysis and machine-learning techniques. Dwivedi et al. ( 2021 ) introduced a multi-parallel adaptive technique to utilise an adaption mechanism in the group of swarms for network intrusion detection. AlEroud and Karabatis ( 2018 ) presented an approach that used contextual information to automatically identify and query possible semantic links between different types of suspicious activities extracted from network flows.

Intrusion detection systems with a focus on IoT

In addition to general intrusion detection systems, a proportion of studies focused on IoT. Habib et al. ( 2020 ) presented an approach for converting traditional intrusion detection systems into smart intrusion detection systems for IoT networks. To enhance the process of diagnostic detection of possible vulnerabilities with an IoT system, Georgescu et al. ( 2019 ) introduced a method that uses a named entity recognition-based solution. With regard to IoT in the smart home sector, Heartfield et al. ( 2021 ) presented a detection system that is able to autonomously adjust the decision function of its underlying anomaly classification models to a smart home’s changing condition. Another intrusion detection system was suggested by Keserwani et al. ( 2021 ), which combined Grey Wolf Optimization and Particle Swam Optimization to identify various attacks for IoT networks. They used the KDD Cup 99, NSL-KDD and CICIDS-2017 to evaluate their model. Abu Al-Haija and Zein-Sabatto ( 2020 ) provide a comprehensive development of a new intelligent and autonomous deep-learning-based detection and classification system for cyberattacks in IoT communication networks that leverage the power of convolutional neural networks, abbreviated as IoT-IDCS-CNN (IoT-based Intrusion Detection and Classification System using Convolutional Neural Network). To evaluate the development, the authors used the NSL-KDD dataset. Biswas and Roy ( 2021 ) recommended a model that identifies malicious botnet traffic using novel deep-learning approaches like artificial neural networks gutted recurrent units and long- or short-term memory models. They tested their model with the Bot-IoT dataset.

With a more forensic background, Koroniotis et al. ( 2020 ) submitted a network forensic framework, which described the digital investigation phases for identifying and tracing attack behaviours in IoT networks. The suggested work was evaluated with the Bot-IoT and UINSW-NB15 datasets. With a focus on big data and IoT, Chhabra et al. ( 2020 ) presented a cyber forensic framework for big data analytics in an IoT environment using machine learning. Furthermore, the authors mentioned different publicly available datasets for machine-learning models.

A stronger focus on a mobile phones was exhibited by Alazab et al. ( 2020 ), which presented a classification model that combined permission requests and application programme interface calls. The model was tested with a malware dataset containing 27,891 Android apps. A similar approach was taken by Li et al. ( 2019a , b ), who proposed a reliable classifier for Android malware detection based on factorisation machine architecture and extraction of Android app features from manifest files and source code.

Literature reviews

In addition to the different methods and models for intrusion detection systems, various literature reviews on the methods and datasets were also found. Liu and Lang ( 2019 ) proposed a taxonomy of intrusion detection systems that uses data objects as the main dimension to classify and summarise machine learning and deep learning-based intrusion detection literature. They also presented four different benchmark datasets for machine-learning detection systems. Ahmed et al. ( 2016 ) presented an in-depth analysis of four major categories of anomaly detection techniques, which include classification, statistical, information theory and clustering. Hajj et al. ( 2021 ) gave a comprehensive overview of anomaly-based intrusion detection systems. Their article gives an overview of the requirements, methods, measurements and datasets that are used in an intrusion detection system.

Within the framework of machine learning, Chattopadhyay et al. ( 2018 ) conducted a comprehensive review and meta-analysis on the application of machine-learning techniques in intrusion detection systems. They also compared different machine learning techniques in different datasets and summarised the performance. Vidros et al. ( 2017 ) presented an overview of characteristics and methods in automatic detection of online recruitment fraud. They also published an available dataset of 17,880 annotated job ads, retrieved from the use of a real-life system. An empirical study of different unsupervised learning algorithms used in the detection of unknown attacks was presented by Meira et al. ( 2020 ).

New datasets

Kilincer et al. ( 2021 ) reviewed different intrusion detection system datasets in detail. They had a closer look at the UNS-NB15, ISCX-2012, NSL-KDD and CIDDS-001 datasets. Stojanovic et al. ( 2020 ) also provided a review on datasets and their creation for use in advanced persistent threat detection in the literature. Another review of datasets was provided by Sarker et al. ( 2020 ), who focused on cybersecurity data science as part of their research and provided an overview from a machine-learning perspective. Avila et al. ( 2021 ) conducted a systematic literature review on the use of security logs for data leak detection. They recommended a new classification of information leak, which uses the GDPR principles, identified the most widely publicly available dataset for threat detection, described the attack types in the datasets and the algorithms used for data leak detection. Tuncer et al. ( 2020 ) presented a bytecode-based detection method consisting of feature extraction using local neighbourhood binary patterns. They chose a byte-based malware dataset to investigate the performance of the proposed local neighbourhood binary pattern-based detection method. With a different focus, Mauro et al. ( 2020 ) gave an experimental overview of neural-based techniques relevant to intrusion detection. They assessed the value of neural networks using the Bot-IoT and UNSW-DB15 datasets.

Another category of results in the context of countermeasure datasets is those that were presented as new. Moreno et al. ( 2018 ) developed a database of 300 security-related accidents from European and American sources. The database contained cybersecurity-related events in the chemical and process industry. Damasevicius et al. ( 2020 ) proposed a new dataset (LITNET-2020) for network intrusion detection. The dataset is a new annotated network benchmark dataset obtained from the real-world academic network. It presents real-world examples of normal and under-attack network traffic. With a focus on IoT intrusion detection systems, Alsaedi et al. ( 2020 ) proposed a new benchmark IoT/IIot datasets for assessing intrusion detection system-enabled IoT systems. Also in the context of IoT, Vaccari et al. ( 2020 ) proposed a dataset focusing on message queue telemetry transport protocols, which can be used to train machine-learning models. To evaluate the performance of machine-learning classifiers, Mahfouz et al. ( 2020 ) created a dataset called Game Theory and Cybersecurity (GTCS). A dataset containing 22,000 malware and benign samples was constructed by Martin et al. ( 2019 ). The dataset can be used as a benchmark to test the algorithm for Android malware classification and clustering techniques. In addition, Laso et al. ( 2017 ) presented a dataset created to investigate how data and information quality estimates enable the detection of anomalies and malicious acts in cyber-physical systems. The dataset contained various cyberattacks and is publicly available.

In addition to the results described above, several other studies were found that fit into the category of countermeasures. Johnson et al. ( 2016 ) examined the time between vulnerability disclosures. Using another vulnerabilities database, Common Vulnerabilities and Exposures (CVE), Subroto and Apriyana ( 2019 ) presented an algorithm model that uses big data analysis of social media and statistical machine learning to predict cyber risks. A similar databank but with a different focus, Common Vulnerability Scoring System, was used by Chatterjee and Thekdi ( 2020 ) to present an iterative data-driven learning approach to vulnerability assessment and management for complex systems. Using the CICIDS2017 dataset to evaluate the performance, Malik et al. ( 2020 ) proposed a control plane-based orchestration for varied, sophisticated threats and attacks. The same dataset was used in another study by Lee et al. ( 2019 ), who developed an artificial security information event management system based on a combination of event profiling for data processing and different artificial network methods. To exploit the interdependence between multiple series, Fang et al. ( 2021 ) proposed a statistical framework. In order to validate the framework, the authors applied it to a dataset of enterprise-level security breaches from the Privacy Rights Clearinghouse and Identity Theft Center database. Another framework with a defensive aspect was recommended by Li et al. ( 2021 ) to increase the robustness of deep neural networks against adversarial malware evasion attacks. Sarabi et al. ( 2016 ) investigated whether and to what extent business details can help assess an organisation's risk of data breaches and the distribution of risk across different types of incidents to create policies for protection, detection and recovery from different forms of security incidents. They used data from the VERIS Community Database.

Datasets that have been classified into the cybersecurity category are detailed in Supplementary Table 3. Due to overlap, records from the previous tables may also be included.

This paper presented a systematic literature review of studies on cyber risk and cybersecurity that used datasets. Within this framework, 255 studies were fully reviewed and then classified into three different categories. Then, 79 datasets were consolidated from these studies. These datasets were subsequently analysed, and important information was selected through a process of filtering out. This information was recorded in a table and enhanced with further information as part of the literature analysis. This made it possible to create a comprehensive overview of the datasets. For example, each dataset contains a description of where the data came from and how the data has been used to date. This allows different datasets to be compared and the appropriate dataset for the use case to be selected. This research certainly has limitations, so our selection of datasets cannot necessarily be taken as a representation of all available datasets related to cyber risks and cybersecurity. For example, literature searches were conducted in four academic databases and only found datasets that were used in the literature. Many research projects also used old datasets that may no longer consider current developments. In addition, the data are often focused on only one observation and are limited in scope. For example, the datasets can only be applied to specific contexts and are also subject to further limitations (e.g. region, industry, operating system). In the context of the applicability of the datasets, it is unfortunately not possible to make a clear statement on the extent to which they can be integrated into academic or practical areas of application or how great this effort is. Finally, it remains to be pointed out that this is an overview of currently available datasets, which are subject to constant change.

Due to the lack of datasets on cyber risks in the academic literature, additional datasets on cyber risks were integrated as part of a further search. The search was conducted on the Google Dataset search portal. The search term used was ‘cyber risk datasets’. Over 100 results were found. However, due to the low significance and verifiability, only 20 selected datasets were included. These can be found in Table 2  in the “ Appendix ”.

The results of the literature review and datasets also showed that there continues to be a lack of available, open cyber datasets. This lack of data is reflected in cyber insurance, for example, as it is difficult to find a risk-based premium without a sufficient database (Nurse et al. 2020 ). The global cyber insurance market was estimated at USD 5.5 billion in 2020 (Dyson 2020 ). When compared to the USD 1 trillion global losses from cybercrime (Maleks Smith et al. 2020 ), it is clear that there exists a significant cyber risk awareness challenge for both the insurance industry and international commerce. Without comprehensive and qualitative data on cyber losses, it can be difficult to estimate potential losses from cyberattacks and price cyber insurance accordingly (GAO 2021 ). For instance, the average cyber insurance loss increased from USD 145,000 in 2019 to USD 359,000 in 2020 (FitchRatings 2021 ). Cyber insurance is an important risk management tool to mitigate the financial impact of cybercrime. This is particularly evident in the impact of different industries. In the Energy & Commodities financial markets, a ransomware attack on the Colonial Pipeline led to a substantial impact on the U.S. economy. As a result of the attack, about 45% of the U.S. East Coast was temporarily unable to obtain supplies of diesel, petrol and jet fuel. This caused the average price in the U.S. to rise 7 cents to USD 3.04 per gallon, the highest in seven years (Garber 2021 ). In addition, Colonial Pipeline confirmed that it paid a USD 4.4 million ransom to a hacker gang after the attack. Another ransomware attack occurred in the healthcare and government sector. The victim of this attack was the Irish Health Service Executive (HSE). A ransom payment of USD 20 million was demanded from the Irish government to restore services after the hack (Tidy 2021 ). In the car manufacturing sector, Miller and Valasek ( 2015 ) initiated a cyberattack that resulted in the recall of 1.4 million vehicles and cost manufacturers EUR 761 million. The risk that arises in the context of these events is the potential for the accumulation of cyber losses, which is why cyber insurers are not expanding their capacity. An example of this accumulation of cyber risks is the NotPetya malware attack, which originated in Russia, struck in Ukraine, and rapidly spread around the world, causing at least USD 10 billion in damage (GAO 2021 ). These events highlight the importance of proper cyber risk management.

This research provides cyber insurance stakeholders with an overview of cyber datasets. Cyber insurers can use the open datasets to improve their understanding and assessment of cyber risks. For example, the impact datasets can be used to better measure financial impacts and their frequencies. These data could be combined with existing portfolio data from cyber insurers and integrated with existing pricing tools and factors to better assess cyber risk valuation. Although most cyber insurers have sparse historical cyber policy and claims data, they remain too small at present for accurate prediction (Bessy-Roland et al. 2021 ). A combination of portfolio data and external datasets would support risk-adjusted pricing for cyber insurance, which would also benefit policyholders. In addition, cyber insurance stakeholders can use the datasets to identify patterns and make better predictions, which would benefit sustainable cyber insurance coverage. In terms of cyber risk cause datasets, cyber insurers can use the data to review their insurance products. For example, the data could provide information on which cyber risks have not been sufficiently considered in product design or where improvements are needed. A combination of cyber cause and cybersecurity datasets can help establish uniform definitions to provide greater transparency and clarity. Consistent terminology could lead to a more sustainable cyber market, where cyber insurers make informed decisions about the level of coverage and policyholders understand their coverage (The Geneva Association 2020).

In addition to the cyber insurance community, this research also supports cybersecurity stakeholders. The reviewed literature can be used to provide a contemporary, contextual and categorised summary of available datasets. This supports efficient and timely progress in cyber risk research and is beneficial given the dynamic nature of cyber risks. With the help of the described cybersecurity datasets and the identified information, a comparison of different datasets is possible. The datasets can be used to evaluate the effectiveness of countermeasures in simulated cyberattacks or to test intrusion detection systems.

In this paper, we conducted a systematic review of studies on cyber risk and cybersecurity databases. We found that most of the datasets are in the field of intrusion detection and machine learning and are used for technical cybersecurity aspects. The available datasets on cyber risks were relatively less represented. Due to the dynamic nature and lack of historical data, assessing and understanding cyber risk is a major challenge for cyber insurance stakeholders. To address this challenge, a greater density of cyber data is needed to support cyber insurers in risk management and researchers with cyber risk-related topics. With reference to ‘Open Science’ FAIR data (Jacobsen et al. 2020 ), mandatory reporting of cyber incidents could help improve cyber understanding, awareness and loss prevention among companies and insurers. Through greater availability of data, cyber risks can be better understood, enabling researchers to conduct more in-depth research into these risks. Companies could incorporate this new knowledge into their corporate culture to reduce cyber risks. For insurance companies, this would have the advantage that all insurers would have the same understanding of cyber risks, which would support sustainable risk-based pricing. In addition, common definitions of cyber risks could be derived from new data.

The cybersecurity databases summarised and categorised in this research could provide a different perspective on cyber risks that would enable the formulation of common definitions in cyber policies. The datasets can help companies addressing cybersecurity and cyber risk as part of risk management assess their internal cyber posture and cybersecurity measures. The paper can also help improve risk awareness and corporate behaviour, and provides the research community with a comprehensive overview of peer-reviewed datasets and other available datasets in the area of cyber risk and cybersecurity. This approach is intended to support the free availability of data for research. The complete tabulated review of the literature is included in the Supplementary Material.

This work provides directions for several paths of future work. First, there are currently few publicly available datasets for cyber risk and cybersecurity. The older datasets that are still widely used no longer reflect today's technical environment. Moreover, they can often only be used in one context, and the scope of the samples is very limited. It would be of great value if more datasets were publicly available that reflect current environmental conditions. This could help intrusion detection systems to consider current events and thus lead to a higher success rate. It could also compensate for the disadvantages of older datasets by collecting larger quantities of samples and making this contextualisation more widespread. Another area of research may be the integratability and adaptability of cybersecurity and cyber risk datasets. For example, it is often unclear to what extent datasets can be integrated or adapted to existing data. For cyber risks and cybersecurity, it would be helpful to know what requirements need to be met or what is needed to use the datasets appropriately. In addition, it would certainly be helpful to know whether datasets can be modified to be used for cyber risks or cybersecurity. Finally, the ability for stakeholders to identify machine-readable cybersecurity datasets would be useful because it would allow for even clearer delineations or comparisons between datasets. Due to the lack of publicly available datasets, concrete benchmarks often cannot be applied.

Average cost of a breach of more than 50 million records.

Aamir, M., S.S.H. Rizvi, M.A. Hashmani, M. Zubair, and J. Ahmad. 2021. Machine learning classification of port scanning and DDoS attacks: A comparative analysis. Mehran University Research Journal of Engineering and Technology 40 (1): 215–229. https://doi.org/10.22581/muet1982.2101.19 .

Article   Google Scholar  

Aamir, M., and S.M.A. Zaidi. 2019. DDoS attack detection with feature engineering and machine learning: The framework and performance evaluation. International Journal of Information Security 18 (6): 761–785. https://doi.org/10.1007/s10207-019-00434-1 .

Aassal, A. El, S. Baki, A. Das, and R.M. Verma. 2020. 2020. An in-depth benchmarking and evaluation of phishing detection research for security needs. IEEE Access 8: 22170–22192. https://doi.org/10.1109/ACCESS.2020.2969780 .

Abu Al-Haija, Q., and S. Zein-Sabatto. 2020. An efficient deep-learning-based detection and classification system for cyber-attacks in IoT communication networks. Electronics 9 (12): 26. https://doi.org/10.3390/electronics9122152 .

Adhikari, U., T.H. Morris, and S.Y. Pan. 2018. Applying Hoeffding adaptive trees for real-time cyber-power event and intrusion classification. IEEE Transactions on Smart Grid 9 (5): 4049–4060. https://doi.org/10.1109/tsg.2017.2647778 .

Agarwal, A., P. Sharma, M. Alshehri, A.A. Mohamed, and O. Alfarraj. 2021. Classification model for accuracy and intrusion detection using machine learning approach. PeerJ Computer Science . https://doi.org/10.7717/peerj-cs.437 .

Agrafiotis, I., J.R.C.. Nurse, M. Goldsmith, S. Creese, and D. Upton. 2018. A taxonomy of cyber-harms: Defining the impacts of cyber-attacks and understanding how they propagate. Journal of Cybersecurity 4: tyy006.

Agrawal, A., S. Mohammed, and J. Fiaidhi. 2019. Ensemble technique for intruder detection in network traffic. International Journal of Security and Its Applications 13 (3): 1–8. https://doi.org/10.33832/ijsia.2019.13.3.01 .

Ahmad, I., and R.A. Alsemmeari. 2020. Towards improving the intrusion detection through ELM (extreme learning machine). CMC Computers Materials & Continua 65 (2): 1097–1111. https://doi.org/10.32604/cmc.2020.011732 .

Ahmed, M., A.N. Mahmood, and J.K. Hu. 2016. A survey of network anomaly detection techniques. Journal of Network and Computer Applications 60: 19–31. https://doi.org/10.1016/j.jnca.2015.11.016 .

Al-Jarrah, O.Y., O. Alhussein, P.D. Yoo, S. Muhaidat, K. Taha, and K. Kim. 2016. Data randomization and cluster-based partitioning for Botnet intrusion detection. IEEE Transactions on Cybernetics 46 (8): 1796–1806. https://doi.org/10.1109/TCYB.2015.2490802 .

Al-Mhiqani, M.N., R. Ahmad, Z.Z. Abidin, W. Yassin, A. Hassan, K.H. Abdulkareem, N.S. Ali, and Z. Yunos. 2020. A review of insider threat detection: Classification, machine learning techniques, datasets, open challenges, and recommendations. Applied Sciences—Basel 10 (15): 41. https://doi.org/10.3390/app10155208 .

Al-Omari, M., M. Rawashdeh, F. Qutaishat, M. Alshira’H, and N. Ababneh. 2021. An intelligent tree-based intrusion detection model for cyber security. Journal of Network and Systems Management 29 (2): 18. https://doi.org/10.1007/s10922-021-09591-y .

Alabdallah, A., and M. Awad. 2018. Using weighted Support Vector Machine to address the imbalanced classes problem of Intrusion Detection System. KSII Transactions on Internet and Information Systems 12 (10): 5143–5158. https://doi.org/10.3837/tiis.2018.10.027 .

Alazab, M., M. Alazab, A. Shalaginov, A. Mesleh, and A. Awajan. 2020. Intelligent mobile malware detection using permission requests and API calls. Future Generation Computer Systems—the International Journal of eScience 107: 509–521. https://doi.org/10.1016/j.future.2020.02.002 .

Albahar, M.A., R.A. Al-Falluji, and M. Binsawad. 2020. An empirical comparison on malicious activity detection using different neural network-based models. IEEE Access 8: 61549–61564. https://doi.org/10.1109/ACCESS.2020.2984157 .

AlEroud, A.F., and G. Karabatis. 2018. Queryable semantics to detect cyber-attacks: A flow-based detection approach. IEEE Transactions on Systems, Man, and Cybernetics: Systems 48 (2): 207–223. https://doi.org/10.1109/TSMC.2016.2600405 .

Algarni, A.M., V. Thayananthan, and Y.K. Malaiya. 2021. Quantitative assessment of cybersecurity risks for mitigating data breaches in business systems. Applied Sciences (switzerland) . https://doi.org/10.3390/app11083678 .

Alhowaide, A., I. Alsmadi, and J. Tang. 2021. Towards the design of real-time autonomous IoT NIDS. Cluster Computing—the Journal of Networks Software Tools and Applications . https://doi.org/10.1007/s10586-021-03231-5 .

Ali, S., and Y. Li. 2019. Learning multilevel auto-encoders for DDoS attack detection in smart grid network. IEEE Access 7: 108647–108659. https://doi.org/10.1109/ACCESS.2019.2933304 .

AlKadi, O., N. Moustafa, B. Turnbull, and K.K.R. Choo. 2019. Mixture localization-based outliers models for securing data migration in cloud centers. IEEE Access 7: 114607–114618. https://doi.org/10.1109/ACCESS.2019.2935142 .

Allianz. 2021. Allianz Risk Barometer. https://www.agcs.allianz.com/content/dam/onemarketing/agcs/agcs/reports/Allianz-Risk-Barometer-2021.pdf . Accessed 15 May 2021.

Almiani, M., A. AbuGhazleh, A. Al-Rahayfeh, S. Atiewi, and Razaque, A. 2020. Deep recurrent neural network for IoT intrusion detection system. Simulation Modelling Practice and Theory 101: 102031. https://doi.org/10.1016/j.simpat.2019.102031

Alsaedi, A., N. Moustafa, Z. Tari, A. Mahmood, and A. Anwar. 2020. TON_IoT telemetry dataset: A new generation dataset of IoT and IIoT for data-driven intrusion detection systems. IEEE Access 8: 165130–165150. https://doi.org/10.1109/access.2020.3022862 .

Alsamiri, J., and K. Alsubhi. 2019. Internet of Things cyber attacks detection using machine learning. International Journal of Advanced Computer Science and Applications 10 (12): 627–634.

Alsharafat, W. 2013. Applying artificial neural network and eXtended classifier system for network intrusion detection. International Arab Journal of Information Technology 10 (3): 230–238.

Google Scholar  

Amin, R.W., H.E. Sevil, S. Kocak, G. Francia III., and P. Hoover. 2021. The spatial analysis of the malicious uniform resource locators (URLs): 2016 dataset case study. Information (switzerland) 12 (1): 1–18. https://doi.org/10.3390/info12010002 .

Arcuri, M.C., L.Z. Gai, F. Ielasi, and E. Ventisette. 2020. Cyber attacks on hospitality sector: Stock market reaction. Journal of Hospitality and Tourism Technology 11 (2): 277–290. https://doi.org/10.1108/jhtt-05-2019-0080 .

Arp, D., M. Spreitzenbarth, M. Hubner, H. Gascon, K. Rieck, and C.E.R.T. Siemens. 2014. Drebin: Effective and explainable detection of android malware in your pocket. In Ndss 14: 23–26.

Ashtiani, M., and M.A. Azgomi. 2014. A distributed simulation framework for modeling cyber attacks and the evaluation of security measures. Simulation 90 (9): 1071–1102. https://doi.org/10.1177/0037549714540221 .

Atefinia, R., and M. Ahmadi. 2021. Network intrusion detection using multi-architectural modular deep neural network. Journal of Supercomputing 77 (4): 3571–3593. https://doi.org/10.1007/s11227-020-03410-y .

Avila, R., R. Khoury, R. Khoury, and F. Petrillo. 2021. Use of security logs for data leak detection: A systematic literature review. Security and Communication Networks 2021: 29. https://doi.org/10.1155/2021/6615899 .

Azeez, N.A., T.J. Ayemobola, S. Misra, R. Maskeliunas, and R. Damasevicius. 2019. Network Intrusion Detection with a Hashing Based Apriori Algorithm Using Hadoop MapReduce. Computers 8 (4): 15. https://doi.org/10.3390/computers8040086 .

Bakdash, J.Z., S. Hutchinson, E.G. Zaroukian, L.R. Marusich, S. Thirumuruganathan, C. Sample, B. Hoffman, and G. Das. 2018. Malware in the future forecasting of analyst detection of cyber events. Journal of Cybersecurity . https://doi.org/10.1093/cybsec/tyy007 .

Barletta, V.S., D. Caivano, A. Nannavecchia, and M. Scalera. 2020. Intrusion detection for in-vehicle communication networks: An unsupervised Kohonen SOM approach. Future Internet . https://doi.org/10.3390/FI12070119 .

Barzegar, M., and M. Shajari. 2018. Attack scenario reconstruction using intrusion semantics. Expert Systems with Applications 108: 119–133. https://doi.org/10.1016/j.eswa.2018.04.030 .

Bessy-Roland, Y., A. Boumezoued, and C. Hillairet. 2021. Multivariate Hawkes process for cyber insurance. Annals of Actuarial Science 15 (1): 14–39.

Bhardwaj, A., V. Mangat, and R. Vig. 2020. Hyperband tuned deep neural network with well posed stacked sparse AutoEncoder for detection of DDoS attacks in cloud. IEEE Access 8: 181916–181929. https://doi.org/10.1109/ACCESS.2020.3028690 .

Bhati, B.S., C.S. Rai, B. Balamurugan, and F. Al-Turjman. 2020. An intrusion detection scheme based on the ensemble of discriminant classifiers. Computers & Electrical Engineering 86: 9. https://doi.org/10.1016/j.compeleceng.2020.106742 .

Bhattacharya, S., S.S.R. Krishnan, P.K.R. Maddikunta, R. Kaluri, S. Singh, T.R. Gadekallu, M. Alazab, and U. Tariq. 2020. A novel PCA-firefly based XGBoost classification model for intrusion detection in networks using GPU. Electronics 9 (2): 16. https://doi.org/10.3390/electronics9020219 .

Bibi, I., A. Akhunzada, J. Malik, J. Iqbal, A. Musaddiq, and S. Kim. 2020. A dynamic DL-driven architecture to combat sophisticated android malware. IEEE Access 8: 129600–129612. https://doi.org/10.1109/ACCESS.2020.3009819 .

Biener, C., M. Eling, and J.H. Wirfs. 2015. Insurability of cyber risk: An empirical analysis. The   Geneva Papers on Risk and Insurance—Issues and Practice 40 (1): 131–158. https://doi.org/10.1057/gpp.2014.19 .

Binbusayyis, A., and T. Vaiyapuri. 2019. Identifying and benchmarking key features for cyber intrusion detection: An ensemble approach. IEEE Access 7: 106495–106513. https://doi.org/10.1109/ACCESS.2019.2929487 .

Biswas, R., and S. Roy. 2021. Botnet traffic identification using neural networks. Multimedia Tools and Applications . https://doi.org/10.1007/s11042-021-10765-8 .

Bouyeddou, B., F. Harrou, B. Kadri, and Y. Sun. 2021. Detecting network cyber-attacks using an integrated statistical approach. Cluster Computing—the Journal of Networks Software Tools and Applications 24 (2): 1435–1453. https://doi.org/10.1007/s10586-020-03203-1 .

Bozkir, A.S., and M. Aydos. 2020. LogoSENSE: A companion HOG based logo detection scheme for phishing web page and E-mail brand recognition. Computers & Security 95: 18. https://doi.org/10.1016/j.cose.2020.101855 .

Brower, D., and M. McCormick. 2021. Colonial pipeline resumes operations following ransomware attack. Financial Times .

Cai, H., F. Zhang, and A. Levi. 2019. An unsupervised method for detecting shilling attacks in recommender systems by mining item relationship and identifying target items. The Computer Journal 62 (4): 579–597. https://doi.org/10.1093/comjnl/bxy124 .

Cebula, J.J., M.E. Popeck, and L.R. Young. 2014. A Taxonomy of Operational Cyber Security Risks Version 2 .

Chadza, T., K.G. Kyriakopoulos, and S. Lambotharan. 2020. Learning to learn sequential network attacks using hidden Markov models. IEEE Access 8: 134480–134497. https://doi.org/10.1109/ACCESS.2020.3011293 .

Chatterjee, S., and S. Thekdi. 2020. An iterative learning and inference approach to managing dynamic cyber vulnerabilities of complex systems. Reliability Engineering and System Safety . https://doi.org/10.1016/j.ress.2019.106664 .

Chattopadhyay, M., R. Sen, and S. Gupta. 2018. A comprehensive review and meta-analysis on applications of machine learning techniques in intrusion detection. Australasian Journal of Information Systems 22: 27.

Chen, H.S., and J. Fiscus. 2018. The inhospitable vulnerability: A need for cybersecurity risk assessment in the hospitality industry. Journal of Hospitality and Tourism Technology 9 (2): 223–234. https://doi.org/10.1108/JHTT-07-2017-0044 .

Chhabra, G.S., V.P. Singh, and M. Singh. 2020. Cyber forensics framework for big data analytics in IoT environment using machine learning. Multimedia Tools and Applications 79 (23–24): 15881–15900. https://doi.org/10.1007/s11042-018-6338-1 .

Chiba, Z., N. Abghour, K. Moussaid, A. Elomri, and M. Rida. 2019. Intelligent approach to build a Deep Neural Network based IDS for cloud environment using combination of machine learning algorithms. Computers and Security 86: 291–317. https://doi.org/10.1016/j.cose.2019.06.013 .

Choras, M., and R. Kozik. 2015. Machine learning techniques applied to detect cyber attacks on web applications. Logic Journal of the IGPL 23 (1): 45–56. https://doi.org/10.1093/jigpal/jzu038 .

Chowdhury, S., M. Khanzadeh, R. Akula, F. Zhang, S. Zhang, H. Medal, M. Marufuzzaman, and L. Bian. 2017. Botnet detection using graph-based feature clustering. Journal of Big Data 4 (1): 14. https://doi.org/10.1186/s40537-017-0074-7 .

Cost Of A Cyber Incident: Systematic Review And Cross-Validation, Cybersecurity & Infrastructure Agency , 1, https://www.cisa.gov/sites/default/files/publications/CISA-OCE_Cost_of_Cyber_Incidents_Study-FINAL_508.pdf (2020).

D’Hooge, L., T. Wauters, B. Volckaert, and F. De Turck. 2019. Classification hardness for supervised learners on 20 years of intrusion detection data. IEEE Access 7: 167455–167469. https://doi.org/10.1109/access.2019.2953451 .

Damasevicius, R., A. Venckauskas, S. Grigaliunas, J. Toldinas, N. Morkevicius, T. Aleliunas, and P. Smuikys. 2020. LITNET-2020: An annotated real-world network flow dataset for network intrusion detection. Electronics 9 (5): 23. https://doi.org/10.3390/electronics9050800 .

De Giovanni, A.L.D., and M. Pirra. 2020. On the determinants of data breaches: A cointegration analysis. Decisions in Economics and Finance . https://doi.org/10.1007/s10203-020-00301-y .

Deng, L., D. Li, X. Yao, and H. Wang. 2019. Retracted Article: Mobile network intrusion detection for IoT system based on transfer learning algorithm. Cluster Computing 22 (4): 9889–9904. https://doi.org/10.1007/s10586-018-1847-2 .

Donkal, G., and G.K. Verma. 2018. A multimodal fusion based framework to reinforce IDS for securing Big Data environment using Spark. Journal of Information Security and Applications 43: 1–11. https://doi.org/10.1016/j.jisa.2018.10.001 .

Dunn, C., N. Moustafa, and B. Turnbull. 2020. Robustness evaluations of sustainable machine learning models against data Poisoning attacks in the Internet of Things. Sustainability 12 (16): 17. https://doi.org/10.3390/su12166434 .

Dwivedi, S., M. Vardhan, and S. Tripathi. 2021. Multi-parallel adaptive grasshopper optimization technique for detecting anonymous attacks in wireless networks. Wireless Personal Communications . https://doi.org/10.1007/s11277-021-08368-5 .

Dyson, B. 2020. COVID-19 crisis could be ‘watershed’ for cyber insurance, says Swiss Re exec. https://www.spglobal.com/marketintelligence/en/news-insights/latest-news-headlines/covid-19-crisis-could-be-watershed-for-cyber-insurance-says-swiss-re-exec-59197154 . Accessed 7 May 2020.

EIOPA. 2018. Understanding cyber insurance—a structured dialogue with insurance companies. https://www.eiopa.europa.eu/sites/default/files/publications/reports/eiopa_understanding_cyber_insurance.pdf . Accessed 28 May 2018

Elijah, A.V., A. Abdullah, N.Z. JhanJhi, M. Supramaniam, and O.B. Abdullateef. 2019. Ensemble and deep-learning methods for two-class and multi-attack anomaly intrusion detection: An empirical study. International Journal of Advanced Computer Science and Applications 10 (9): 520–528.

Eling, M., and K. Jung. 2018. Copula approaches for modeling cross-sectional dependence of data breach losses. Insurance Mathematics & Economics 82: 167–180. https://doi.org/10.1016/j.insmatheco.2018.07.003 .

Eling, M., and W. Schnell. 2016. What do we know about cyber risk and cyber risk insurance? Journal of Risk Finance 17 (5): 474–491. https://doi.org/10.1108/jrf-09-2016-0122 .

Eling, M., and J. Wirfs. 2019. What are the actual costs of cyber risk events? European Journal of Operational Research 272 (3): 1109–1119. https://doi.org/10.1016/j.ejor.2018.07.021 .

Eling, M. 2020. Cyber risk research in business and actuarial science. European Actuarial Journal 10 (2): 303–333.

Elmasry, W., A. Akbulut, and A.H. Zaim. 2019. Empirical study on multiclass classification-based network intrusion detection. Computational Intelligence 35 (4): 919–954. https://doi.org/10.1111/coin.12220 .

Elsaid, S.A., and N.S. Albatati. 2020. An optimized collaborative intrusion detection system for wireless sensor networks. Soft Computing 24 (16): 12553–12567. https://doi.org/10.1007/s00500-020-04695-0 .

Estepa, R., J.E. Díaz-Verdejo, A. Estepa, and G. Madinabeitia. 2020. How much training data is enough? A case study for HTTP anomaly-based intrusion detection. IEEE Access 8: 44410–44425. https://doi.org/10.1109/ACCESS.2020.2977591 .

European Council. 2021. Cybersecurity: how the EU tackles cyber threats. https://www.consilium.europa.eu/en/policies/cybersecurity/ . Accessed 10 May 2021

Falco, G. et al. 2019. Cyber risk research impeded by disciplinary barriers. Science (American Association for the Advancement of Science) 366 (6469): 1066–1069.

Fan, Z.J., Z.P. Tan, C.X. Tan, and X. Li. 2018. An improved integrated prediction method of cyber security situation based on spatial-time analysis. Journal of Internet Technology 19 (6): 1789–1800. https://doi.org/10.3966/160792642018111906015 .

Fang, Z.J., M.C. Xu, S.H. Xu, and T.Z. Hu. 2021. A framework for predicting data breach risk: Leveraging dependence to cope with sparsity. IEEE Transactions on Information Forensics and Security 16: 2186–2201. https://doi.org/10.1109/tifs.2021.3051804 .

Farkas, S., O. Lopez, and M. Thomas. 2021. Cyber claim analysis using Generalized Pareto regression trees with applications to insurance. Insurance: Mathematics and Economics 98: 92–105. https://doi.org/10.1016/j.insmatheco.2021.02.009 .

Farsi, H., A. Fanian, and Z. Taghiyarrenani. 2019. A novel online state-based anomaly detection system for process control networks. International Journal of Critical Infrastructure Protection 27: 11. https://doi.org/10.1016/j.ijcip.2019.100323 .

Ferrag, M.A., L. Maglaras, S. Moschoyiannis, and H. Janicke. 2020. Deep learning for cyber security intrusion detection: Approaches, datasets, and comparative study. Journal of Information Security and Applications 50: 19. https://doi.org/10.1016/j.jisa.2019.102419 .

Field, M. 2018. WannaCry cyber attack cost the NHS £92m as 19,000 appointments cancelled. https://www.telegraph.co.uk/technology/2018/10/11/wannacry-cyber-attack-cost-nhs-92m-19000-appointments-cancelled/ . Accessed 9 May 2018.

FitchRatings. 2021. U.S. Cyber Insurance Market Update (Spike in Claims Leads to Decline in 2020 Underwriting Performance). https://www.fitchratings.com/research/insurance/us-cyber-insurance-market-update-spike-in-claims-leads-to-decline-in-2020-underwriting-performance-26-05-2021 .

Fossaceca, J.M., T.A. Mazzuchi, and S. Sarkani. 2015. MARK-ELM: Application of a novel Multiple Kernel Learning framework for improving the robustness of network intrusion detection. Expert Systems with Applications 42 (8): 4062–4080. https://doi.org/10.1016/j.eswa.2014.12.040 .

Franke, U., and J. Brynielsson. 2014. Cyber situational awareness–a systematic review of the literature. Computers & security 46: 18–31.

Freeha, K., K.J. Hwan, M. Lars, and M. Robin. 2021. Data breach management: An integrated risk model. Information & Management 58 (1): 103392. https://doi.org/10.1016/j.im.2020.103392 .

Ganeshan, R., and P. Rodrigues. 2020. Crow-AFL: Crow based adaptive fractional lion optimization approach for the intrusion detection. Wireless Personal Communications 111 (4): 2065–2089. https://doi.org/10.1007/s11277-019-06972-0 .

GAO. 2021. CYBER INSURANCE—Insurers and policyholders face challenges in an evolving market. https://www.gao.gov/assets/gao-21-477.pdf . Accessed 16 May 2021.

Garber, J. 2021. Colonial Pipeline fiasco foreshadows impact of Biden energy policy. https://www.foxbusiness.com/markets/colonial-pipeline-fiasco-foreshadows-impact-of-biden-energy-policy . Accessed 4 May 2021.

Gauthama Raman, M.R., N. Somu, S. Jagarapu, T. Manghnani, T. Selvam, K. Krithivasan, and V.S. Shankar Sriram. 2020. An efficient intrusion detection technique based on support vector machine and improved binary gravitational search algorithm. Artificial Intelligence Review 53 (5): 3255–3286. https://doi.org/10.1007/s10462-019-09762-z .

Gavel, S., A.S. Raghuvanshi, and S. Tiwari. 2021. Distributed intrusion detection scheme using dual-axis dimensionality reduction for Internet of things (IoT). Journal of Supercomputing . https://doi.org/10.1007/s11227-021-03697-5 .

GDPR.EU. 2021. FAQ. https://gdpr.eu/faq/ . Accessed 10 May 2021.

Georgescu, T.M., B. Iancu, and M. Zurini. 2019. Named-entity-recognition-based automated system for diagnosing cybersecurity situations in IoT networks. Sensors (switzerland) . https://doi.org/10.3390/s19153380 .

Giudici, P., and E. Raffinetti. 2020. Cyber risk ordering with rank-based statistical models. AStA Advances in Statistical Analysis . https://doi.org/10.1007/s10182-020-00387-0 .

Goh, J., S. Adepu, K.N. Junejo, and A. Mathur. 2016. A dataset to support research in the design of secure water treatment systems. In CRITIS.

Gong, X.Y., J.L. Lu, Y.F. Zhou, H. Qiu, and R. He. 2021. Model uncertainty based annotation error fixing for web attack detection. Journal of Signal Processing Systems for Signal Image and Video Technology 93 (2–3): 187–199. https://doi.org/10.1007/s11265-019-01494-1 .

Goode, S., H. Hoehle, V. Venkatesh, and S.A. Brown. 2017. USER compensation as a data breach recovery action: An investigation of the sony playstation network breach. MIS Quarterly 41 (3): 703–727.

Guo, H., S. Huang, C. Huang, Z. Pan, M. Zhang, and F. Shi. 2020. File entropy signal analysis combined with wavelet decomposition for malware classification. IEEE Access 8: 158961–158971. https://doi.org/10.1109/ACCESS.2020.3020330 .

Habib, M., I. Aljarah, and H. Faris. 2020. A Modified multi-objective particle swarm optimizer-based Lévy flight: An approach toward intrusion detection in Internet of Things. Arabian Journal for Science and Engineering 45 (8): 6081–6108. https://doi.org/10.1007/s13369-020-04476-9 .

Hajj, S., R. El Sibai, J.B. Abdo, J. Demerjian, A. Makhoul, and C. Guyeux. 2021. Anomaly-based intrusion detection systems: The requirements, methods, measurements, and datasets. Transactions on Emerging Telecommunications Technologies 32 (4): 36. https://doi.org/10.1002/ett.4240 .

Heartfield, R., G. Loukas, A. Bezemskij, and E. Panaousis. 2021. Self-configurable cyber-physical intrusion detection for smart homes using reinforcement learning. IEEE Transactions on Information Forensics and Security 16: 1720–1735. https://doi.org/10.1109/tifs.2020.3042049 .

Hemo, B., T. Gafni, K. Cohen, and Q. Zhao. 2020. Searching for anomalies over composite hypotheses. IEEE Transactions on Signal Processing 68: 1181–1196. https://doi.org/10.1109/TSP.2020.2971438

Hindy, H., D. Brosset, E. Bayne, A.K. Seeam, C. Tachtatzis, R. Atkinson, and X. Bellekens. 2020. A taxonomy of network threats and the effect of current datasets on intrusion detection systems. IEEE Access 8: 104650–104675. https://doi.org/10.1109/ACCESS.2020.3000179 .

Hong, W., D. Huang, C. Chen, and J. Lee. 2020. Towards accurate and efficient classification of power system contingencies and cyber-attacks using recurrent neural networks. IEEE Access 8: 123297–123309. https://doi.org/10.1109/ACCESS.2020.3007609 .

Husák, M., M. Zádník, V. Bartos, and P. Sokol. 2020. Dataset of intrusion detection alerts from a sharing platform. Data in Brief 33: 106530.

IBM Security. 2020. Cost of a Data breach Report. https://www.capita.com/sites/g/files/nginej291/files/2020-08/Ponemon-Global-Cost-of-Data-Breach-Study-2020.pdf . Accessed 19 May 2021.

IEEE. 2021. IEEE Quick Facts. https://www.ieee.org/about/at-a-glance.html . Accessed 11 May 2021.

Kilincer, I.F., F. Ertam, and S. Abdulkadir. 2021. Machine learning methods for cyber security intrusion detection: Datasets and comparative study. Computer Networks 188: 107840. https://doi.org/10.1016/j.comnet.2021.107840 .

Jaber, A.N., and S. Ul Rehman. 2020. FCM-SVM based intrusion detection system for cloud computing environment. Cluster Computing—the Journal of Networks Software Tools and Applications 23 (4): 3221–3231. https://doi.org/10.1007/s10586-020-03082-6 .

Jacobs, J., S. Romanosky, B. Edwards, M. Roytman, and I. Adjerid. 2019. Exploit prediction scoring system (epss). arXiv:1908.04856

Jacobsen, A. et al. 2020. FAIR principles: Interpretations and implementation considerations. Data Intelligence 2 (1–2): 10–29. https://doi.org/10.1162/dint_r_00024 .

Jahromi, A.N., S. Hashemi, A. Dehghantanha, R.M. Parizi, and K.K.R. Choo. 2020. An enhanced stacked LSTM method with no random initialization for malware threat hunting in safety and time-critical systems. IEEE Transactions on Emerging Topics in Computational Intelligence 4 (5): 630–640. https://doi.org/10.1109/TETCI.2019.2910243 .

Jang, S., S. Li, and Y. Sung. 2020. FastText-based local feature visualization algorithm for merged image-based malware classification framework for cyber security and cyber defense. Mathematics 8 (3): 13. https://doi.org/10.3390/math8030460 .

Javeed, D., T.H. Gao, and M.T. Khan. 2021. SDN-enabled hybrid DL-driven framework for the detection of emerging cyber threats in IoT. Electronics 10 (8): 16. https://doi.org/10.3390/electronics10080918 .

Johnson, P., D. Gorton, R. Lagerstrom, and M. Ekstedt. 2016. Time between vulnerability disclosures: A measure of software product vulnerability. Computers & Security 62: 278–295. https://doi.org/10.1016/j.cose.2016.08.004 .

Johnson, P., R. Lagerström, M. Ekstedt, and U. Franke. 2018. Can the common vulnerability scoring system be trusted? A Bayesian analysis. IEEE Transactions on Dependable and Secure Computing 15 (6): 1002–1015. https://doi.org/10.1109/TDSC.2016.2644614 .

Junger, M., V. Wang, and M. Schlömer. 2020. Fraud against businesses both online and offline: Crime scripts, business characteristics, efforts, and benefits. Crime Science 9 (1): 13. https://doi.org/10.1186/s40163-020-00119-4 .

Kalutarage, H.K., H.N. Nguyen, and S.A. Shaikh. 2017. Towards a threat assessment framework for apps collusion. Telecommunication Systems 66 (3): 417–430. https://doi.org/10.1007/s11235-017-0296-1 .

Kamarudin, M.H., C. Maple, T. Watson, and N.S. Safa. 2017. A LogitBoost-based algorithm for detecting known and unknown web attacks. IEEE Access 5: 26190–26200. https://doi.org/10.1109/ACCESS.2017.2766844 .

Kasongo, S.M., and Y.X. Sun. 2020. A deep learning method with wrapper based feature extraction for wireless intrusion detection system. Computers & Security 92: 15. https://doi.org/10.1016/j.cose.2020.101752 .

Keserwani, P.K., M.C. Govil, E.S. Pilli, and P. Govil. 2021. A smart anomaly-based intrusion detection system for the Internet of Things (IoT) network using GWO–PSO–RF model. Journal of Reliable Intelligent Environments 7 (1): 3–21. https://doi.org/10.1007/s40860-020-00126-x .

Keshk, M., E. Sitnikova, N. Moustafa, J. Hu, and I. Khalil. 2021. An integrated framework for privacy-preserving based anomaly detection for cyber-physical systems. IEEE Transactions on Sustainable Computing 6 (1): 66–79. https://doi.org/10.1109/TSUSC.2019.2906657 .

Khan, I.A., D.C. Pi, A.K. Bhatia, N. Khan, W. Haider, and A. Wahab. 2020. Generating realistic IoT-based IDS dataset centred on fuzzy qualitative modelling for cyber-physical systems. Electronics Letters 56 (9): 441–443. https://doi.org/10.1049/el.2019.4158 .

Khraisat, A., I. Gondal, P. Vamplew, J. Kamruzzaman, and A. Alazab. 2020. Hybrid intrusion detection system based on the stacking ensemble of C5 decision tree classifier and one class support vector machine. Electronics 9 (1): 18. https://doi.org/10.3390/electronics9010173 .

Khraisat, A., I. Gondal, P. Vamplew, and J. Kamruzzaman. 2019. Survey of intrusion detection systems: Techniques, datasets and challenges. Cybersecurity 2 (1): 20. https://doi.org/10.1186/s42400-019-0038-7 .

Kilincer, I.F., F. Ertam, and A. Sengur. 2021. Machine learning methods for cyber security intrusion detection: Datasets and comparative study. Computer Networks 188: 16. https://doi.org/10.1016/j.comnet.2021.107840 .

Kim, D., and H.K. Kim. 2019. Automated dataset generation system for collaborative research of cyber threat analysis. Security and Communication Networks 2019: 10. https://doi.org/10.1155/2019/6268476 .

Kim, G., C. Lee, J. Jo, and H. Lim. 2020. Automatic extraction of named entities of cyber threats using a deep Bi-LSTM-CRF network. International Journal of Machine Learning and Cybernetics 11 (10): 2341–2355. https://doi.org/10.1007/s13042-020-01122-6 .

Kirubavathi, G., and R. Anitha. 2016. Botnet detection via mining of traffic flow characteristics. Computers & Electrical Engineering 50: 91–101. https://doi.org/10.1016/j.compeleceng.2016.01.012 .

Kiwia, D., A. Dehghantanha, K.K.R. Choo, and J. Slaughter. 2018. A cyber kill chain based taxonomy of banking Trojans for evolutionary computational intelligence. Journal of Computational Science 27: 394–409. https://doi.org/10.1016/j.jocs.2017.10.020 .

Koroniotis, N., N. Moustafa, and E. Sitnikova. 2020. A new network forensic framework based on deep learning for Internet of Things networks: A particle deep framework. Future Generation Computer Systems 110: 91–106. https://doi.org/10.1016/j.future.2020.03.042 .

Kruse, C.S., B. Frederick, T. Jacobson, and D. Kyle Monticone. 2017. Cybersecurity in healthcare: A systematic review of modern threats and trends. Technology and Health Care 25 (1): 1–10.

Kshetri, N. 2018. The economics of cyber-insurance. IT Professional 20 (6): 9–14. https://doi.org/10.1109/MITP.2018.2874210 .

Kumar, R., P. Kumar, R. Tripathi, G.P. Gupta, T.R. Gadekallu, and G. Srivastava. 2021. SP2F: A secured privacy-preserving framework for smart agricultural Unmanned Aerial Vehicles. Computer Networks . https://doi.org/10.1016/j.comnet.2021.107819 .

Kumar, R., and R. Tripathi. 2021. DBTP2SF: A deep blockchain-based trustworthy privacy-preserving secured framework in industrial internet of things systems. Transactions on Emerging Telecommunications Technologies 32 (4): 27. https://doi.org/10.1002/ett.4222 .

Laso, P.M., D. Brosset, and J. Puentes. 2017. Dataset of anomalies and malicious acts in a cyber-physical subsystem. Data in Brief 14: 186–191. https://doi.org/10.1016/j.dib.2017.07.038 .

Lee, J., J. Kim, I. Kim, and K. Han. 2019. Cyber threat detection based on artificial neural networks using event profiles. IEEE Access 7: 165607–165626. https://doi.org/10.1109/ACCESS.2019.2953095 .

Lee, S.J., P.D. Yoo, A.T. Asyhari, Y. Jhi, L. Chermak, C.Y. Yeun, and K. Taha. 2020. IMPACT: Impersonation attack detection via edge computing using deep Autoencoder and feature abstraction. IEEE Access 8: 65520–65529. https://doi.org/10.1109/ACCESS.2020.2985089 .

Leong, Y.-Y., and Y.-C. Chen. 2020. Cyber risk cost and management in IoT devices-linked health insurance. The Geneva Papers on Risk and Insurance—Issues and Practice 45 (4): 737–759. https://doi.org/10.1057/s41288-020-00169-4 .

Levi, M. 2017. Assessing the trends, scale and nature of economic cybercrimes: overview and Issues: In Cybercrimes, cybercriminals and their policing, in crime, law and social change. Crime, Law and Social Change 67 (1): 3–20. https://doi.org/10.1007/s10611-016-9645-3 .

Li, C., K. Mills, D. Niu, R. Zhu, H. Zhang, and H. Kinawi. 2019a. Android malware detection based on factorization machine. IEEE Access 7: 184008–184019. https://doi.org/10.1109/ACCESS.2019.2958927 .

Li, D.Q., and Q.M. Li. 2020. Adversarial deep ensemble: evasion attacks and defenses for malware detection. IEEE Transactions on Information Forensics and Security 15: 3886–3900. https://doi.org/10.1109/tifs.2020.3003571 .

Li, D.Q., Q.M. Li, Y.F. Ye, and S.H. Xu. 2021. A framework for enhancing deep neural networks against adversarial malware. IEEE Transactions on Network Science and Engineering 8 (1): 736–750. https://doi.org/10.1109/tnse.2021.3051354 .

Li, R.H., C. Zhang, C. Feng, X. Zhang, and C.J. Tang. 2019b. Locating vulnerability in binaries using deep neural networks. IEEE Access 7: 134660–134676. https://doi.org/10.1109/access.2019.2942043 .

Li, X., M. Xu, P. Vijayakumar, N. Kumar, and X. Liu. 2020. Detection of low-frequency and multi-stage attacks in industrial Internet of Things. IEEE Transactions on Vehicular Technology 69 (8): 8820–8831. https://doi.org/10.1109/TVT.2020.2995133 .

Liu, H.Y., and B. Lang. 2019. Machine learning and deep learning methods for intrusion detection systems: A survey. Applied Sciences—Basel 9 (20): 28. https://doi.org/10.3390/app9204396 .

Lopez-Martin, M., B. Carro, and A. Sanchez-Esguevillas. 2020. Application of deep reinforcement learning to intrusion detection for supervised problems. Expert Systems with Applications . https://doi.org/10.1016/j.eswa.2019.112963 .

Loukas, G., D. Gan, and Tuan Vuong. 2013. A review of cyber threats and defence approaches in emergency management. Future Internet 5: 205–236.

Luo, C.C., S. Su, Y.B. Sun, Q.J. Tan, M. Han, and Z.H. Tian. 2020. A convolution-based system for malicious URLs detection. CMC—Computers Materials Continua 62 (1): 399–411.

Mahbooba, B., M. Timilsina, R. Sahal, and M. Serrano. 2021. Explainable artificial intelligence (XAI) to enhance trust management in intrusion detection systems using decision tree model. Complexity 2021: 11. https://doi.org/10.1155/2021/6634811 .

Mahdavifar, S., and A.A. Ghorbani. 2020. DeNNeS: Deep embedded neural network expert system for detecting cyber attacks. Neural Computing & Applications 32 (18): 14753–14780. https://doi.org/10.1007/s00521-020-04830-w .

Mahfouz, A., A. Abuhussein, D. Venugopal, and S. Shiva. 2020. Ensemble classifiers for network intrusion detection using a novel network attack dataset. Future Internet 12 (11): 1–19. https://doi.org/10.3390/fi12110180 .

Maleks Smith, Z., E. Lostri, and J.A. Lewis. 2020. The hidden costs of cybercrime. https://www.mcafee.com/enterprise/en-us/assets/reports/rp-hidden-costs-of-cybercrime.pdf . Accessed 16 May 2021.

Malik, J., A. Akhunzada, I. Bibi, M. Imran, A. Musaddiq, and S.W. Kim. 2020. Hybrid deep learning: An efficient reconnaissance and surveillance detection mechanism in SDN. IEEE Access 8: 134695–134706. https://doi.org/10.1109/ACCESS.2020.3009849 .

Manimurugan, S. 2020. IoT-Fog-Cloud model for anomaly detection using improved Naive Bayes and principal component analysis. Journal of Ambient Intelligence and Humanized Computing . https://doi.org/10.1007/s12652-020-02723-3 .

Martin, A., R. Lara-Cabrera, and D. Camacho. 2019. Android malware detection through hybrid features fusion and ensemble classifiers: The AndroPyTool framework and the OmniDroid dataset. Information Fusion 52: 128–142. https://doi.org/10.1016/j.inffus.2018.12.006 .

Mauro, M.D., G. Galatro, and A. Liotta. 2020. Experimental review of neural-based approaches for network intrusion management. IEEE Transactions on Network and Service Management 17 (4): 2480–2495. https://doi.org/10.1109/TNSM.2020.3024225 .

McLeod, A., and D. Dolezel. 2018. Cyber-analytics: Modeling factors associated with healthcare data breaches. Decision Support Systems 108: 57–68. https://doi.org/10.1016/j.dss.2018.02.007 .

Meira, J., R. Andrade, I. Praca, J. Carneiro, V. Bolon-Canedo, A. Alonso-Betanzos, and G. Marreiros. 2020. Performance evaluation of unsupervised techniques in cyber-attack anomaly detection. Journal of Ambient Intelligence and Humanized Computing 11 (11): 4477–4489. https://doi.org/10.1007/s12652-019-01417-9 .

Miao, Y., J. Ma, X. Liu, J. Weng, H. Li, and H. Li. 2019. Lightweight fine-grained search over encrypted data in Fog computing. IEEE Transactions on Services Computing 12 (5): 772–785. https://doi.org/10.1109/TSC.2018.2823309 .

Miller, C., and C. Valasek. 2015. Remote exploitation of an unaltered passenger vehicle. Black Hat USA 2015 (S 91).

Mireles, J.D., E. Ficke, J.H. Cho, P. Hurley, and S.H. Xu. 2019. Metrics towards measuring cyber agility. IEEE Transactions on Information Forensics and Security 14 (12): 3217–3232. https://doi.org/10.1109/tifs.2019.2912551 .

Mishra, N., and S. Pandya. 2021. Internet of Things applications, security challenges, attacks, intrusion detection, and future visions: A systematic review. IEEE Access . https://doi.org/10.1109/ACCESS.2021.3073408 .

Monshizadeh, M., V. Khatri, B.G. Atli, R. Kantola, and Z. Yan. 2019. Performance evaluation of a combined anomaly detection platform. IEEE Access 7: 100964–100978. https://doi.org/10.1109/ACCESS.2019.2930832 .

Moreno, V.C., G. Reniers, E. Salzano, and V. Cozzani. 2018. Analysis of physical and cyber security-related events in the chemical and process industry. Process Safety and Environmental Protection 116: 621–631. https://doi.org/10.1016/j.psep.2018.03.026 .

Moro, E.D. 2020. Towards an economic cyber loss index for parametric cover based on IT security indicator: A preliminary analysis. Risks . https://doi.org/10.3390/risks8020045 .

Moustafa, N., E. Adi, B. Turnbull, and J. Hu. 2018. A new threat intelligence scheme for safeguarding industry 4.0 systems. IEEE Access 6: 32910–32924. https://doi.org/10.1109/ACCESS.2018.2844794 .

Moustakidis, S., and P. Karlsson. 2020. A novel feature extraction methodology using Siamese convolutional neural networks for intrusion detection. Cybersecurity . https://doi.org/10.1186/s42400-020-00056-4 .

Mukhopadhyay, A., S. Chatterjee, K.K. Bagchi, P.J. Kirs, and G.K. Shukla. 2019. Cyber Risk Assessment and Mitigation (CRAM) framework using Logit and Probit models for cyber insurance. Information Systems Frontiers 21 (5): 997–1018. https://doi.org/10.1007/s10796-017-9808-5 .

Murphey, H. 2021a. Biden signs executive order to strengthen US cyber security. https://www.ft.com/content/4d808359-b504-4014-85f6-68e7a2851bf1?accessToken=zwAAAXl0_ifgkc9NgINZtQRAFNOF9mjnooUb8Q.MEYCIQDw46SFWsMn1iyuz3kvgAmn6mxc0rIVfw10Lg1ovJSfJwIhAK2X2URzfSqHwIS7ddRCvSt2nGC2DcdoiDTG49-4TeEt&sharetype=gift?token=fbcd6323-1ecf-4fc3-b136-b5b0dd6a8756 . Accessed 7 May 2021.

Murphey, H. 2021b. Millions of connected devices have security flaws, study shows. https://www.ft.com/content/0bf92003-926d-4dee-87d7-b01f7c3e9621?accessToken=zwAAAXnA7f2Ikc8L-SADkm1N7tOH17AffD6WIQ.MEQCIDjBuROvhmYV0Mx3iB0cEV7m5oND1uaCICxJu0mzxM0PAiBam98q9zfHiTB6hKGr1gGl0Azt85yazdpX9K5sI8se3Q&sharetype=gift?token=2538218d-77d9-4dd3-9649-3cb556a34e51 . Accessed 6 May 2021.

Murugesan, V., M. Shalinie, and M.H. Yang. 2018. Design and analysis of hybrid single packet IP traceback scheme. IET Networks 7 (3): 141–151. https://doi.org/10.1049/iet-net.2017.0115 .

Mwitondi, K.S., and S.A. Zargari. 2018. An iterative multiple sampling method for intrusion detection. Information Security Journal 27 (4): 230–239. https://doi.org/10.1080/19393555.2018.1539790 .

Neto, N.N., S. Madnick, A.M.G. De Paula, and N.M. Borges. 2021. Developing a global data breach database and the challenges encountered. ACM Journal of Data and Information Quality 13 (1): 33. https://doi.org/10.1145/3439873 .

Nurse, J.R.C., L. Axon, A. Erola, I. Agrafiotis, M. Goldsmith, and S. Creese. 2020. The data that drives cyber insurance: A study into the underwriting and claims processes. In 2020 International conference on cyber situational awareness, data analytics and assessment (CyberSA), 15–19 June 2020.

Oliveira, N., I. Praca, E. Maia, and O. Sousa. 2021. Intelligent cyber attack detection and classification for network-based intrusion detection systems. Applied Sciences—Basel 11 (4): 21. https://doi.org/10.3390/app11041674 .

Page, M.J. et al. 2021. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. Systematic Reviews 10 (1): 89. https://doi.org/10.1186/s13643-021-01626-4 .

Pajouh, H.H., R. Javidan, R. Khayami, A. Dehghantanha, and K.R. Choo. 2019. A two-layer dimension reduction and two-tier classification model for anomaly-based intrusion detection in IoT backbone networks. IEEE Transactions on Emerging Topics in Computing 7 (2): 314–323. https://doi.org/10.1109/TETC.2016.2633228 .

Parra, G.D., P. Rad, K.K.R. Choo, and N. Beebe. 2020. Detecting Internet of Things attacks using distributed deep learning. Journal of Network and Computer Applications 163: 13. https://doi.org/10.1016/j.jnca.2020.102662 .

Paté-Cornell, M.E., M. Kuypers, M. Smith, and P. Keller. 2018. Cyber risk management for critical infrastructure: A risk analysis model and three case studies. Risk Analysis 38 (2): 226–241. https://doi.org/10.1111/risa.12844 .

Pooser, D.M., M.J. Browne, and O. Arkhangelska. 2018. Growth in the perception of cyber risk: evidence from U.S. P&C Insurers. The Geneva Papers on Risk and Insurance—Issues and Practice 43 (2): 208–223. https://doi.org/10.1057/s41288-017-0077-9 .

Pu, G., L. Wang, J. Shen, and F. Dong. 2021. A hybrid unsupervised clustering-based anomaly detection method. Tsinghua Science and Technology 26 (2): 146–153. https://doi.org/10.26599/TST.2019.9010051 .

Qiu, J., W. Luo, L. Pan, Y. Tai, J. Zhang, and Y. Xiang. 2019. Predicting the impact of android malicious samples via machine learning. IEEE Access 7: 66304–66316. https://doi.org/10.1109/ACCESS.2019.2914311 .

Qu, X., L. Yang, K. Guo, M. Sun, L. Ma, T. Feng, S. Ren, K. Li, and X. Ma. 2020. Direct batch growth hierarchical self-organizing mapping based on statistics for efficient network intrusion detection. IEEE Access 8: 42251–42260. https://doi.org/10.1109/ACCESS.2020.2976810 .

Rahman, Md.S., S. Halder, Md. Ashraf Uddin, and U.K. Acharjee. 2021. An efficient hybrid system for anomaly detection in social networks. Cybersecurity 4 (1): 10. https://doi.org/10.1186/s42400-021-00074-w .

Ramaiah, M., V. Chandrasekaran, V. Ravi, and N. Kumar. 2021. An intrusion detection system using optimized deep neural network architecture. Transactions on Emerging Telecommunications Technologies 32 (4): 17. https://doi.org/10.1002/ett.4221 .

Raman, M.R.G., K. Kannan, S.K. Pal, and V.S.S. Sriram. 2016. Rough set-hypergraph-based feature selection approach for intrusion detection systems. Defence Science Journal 66 (6): 612–617. https://doi.org/10.14429/dsj.66.10802 .

Rathore, S., J.H. Park. 2018. Semi-supervised learning based distributed attack detection framework for IoT. Applied Soft Computing 72: 79–89. https://doi.org/10.1016/j.asoc.2018.05.049 .

Romanosky, S., L. Ablon, A. Kuehn, and T. Jones. 2019. Content analysis of cyber insurance policies: How do carriers price cyber risk? Journal of Cybersecurity (oxford) 5 (1): tyz002.

Sarabi, A., P. Naghizadeh, Y. Liu, and M. Liu. 2016. Risky business: Fine-grained data breach prediction using business profiles. Journal of Cybersecurity 2 (1): 15–28. https://doi.org/10.1093/cybsec/tyw004 .

Sardi, Alberto, Alessandro Rizzi, Enrico Sorano, and Anna Guerrieri. 2021. Cyber risk in health facilities: A systematic literature review. Sustainability 12 (17): 7002.

Sarker, Iqbal H., A.S.M. Kayes, Shahriar Badsha, Hamed Alqahtani, Paul Watters, and Alex Ng. 2020. Cybersecurity data science: An overview from machine learning perspective. Journal of Big Data 7 (1): 41. https://doi.org/10.1186/s40537-020-00318-5 .

Scopus. 2021. Factsheet. https://www.elsevier.com/__data/assets/pdf_file/0017/114533/Scopus_GlobalResearch_Factsheet2019_FINAL_WEB.pdf . Accessed 11 May 2021.

Sentuna, A., A. Alsadoon, P.W.C. Prasad, M. Saadeh, and O.H. Alsadoon. 2021. A novel Enhanced Naïve Bayes Posterior Probability (ENBPP) using machine learning: Cyber threat analysis. Neural Processing Letters 53 (1): 177–209. https://doi.org/10.1007/s11063-020-10381-x .

Shaukat, K., S.H. Luo, V. Varadharajan, I.A. Hameed, S. Chen, D.X. Liu, and J.M. Li. 2020. Performance comparison and current challenges of using machine learning techniques in cybersecurity. Energies 13 (10): 27. https://doi.org/10.3390/en13102509 .

Sheehan, B., F. Murphy, M. Mullins, and C. Ryan. 2019. Connected and autonomous vehicles: A cyber-risk classification framework. Transportation Research Part a: Policy and Practice 124: 523–536. https://doi.org/10.1016/j.tra.2018.06.033 .

Sheehan, B., F. Murphy, A.N. Kia, and R. Kiely. 2021. A quantitative bow-tie cyber risk classification and assessment framework. Journal of Risk Research 24 (12): 1619–1638.

Shlomo, A., M. Kalech, and R. Moskovitch. 2021. Temporal pattern-based malicious activity detection in SCADA systems. Computers & Security 102: 17. https://doi.org/10.1016/j.cose.2020.102153 .

Singh, K.J., and T. De. 2020. Efficient classification of DDoS attacks using an ensemble feature selection algorithm. Journal of Intelligent Systems 29 (1): 71–83. https://doi.org/10.1515/jisys-2017-0472 .

Skrjanc, I., S. Ozawa, T. Ban, and D. Dovzan. 2018. Large-scale cyber attacks monitoring using Evolving Cauchy Possibilistic Clustering. Applied Soft Computing 62: 592–601. https://doi.org/10.1016/j.asoc.2017.11.008 .

Smart, W. 2018. Lessons learned review of the WannaCry Ransomware Cyber Attack. https://www.england.nhs.uk/wp-content/uploads/2018/02/lessons-learned-review-wannacry-ransomware-cyber-attack-cio-review.pdf . Accessed 7 May 2021.

Sornette, D., T. Maillart, and W. Kröger. 2013. Exploring the limits of safety analysis in complex technological systems. International Journal of Disaster Risk Reduction 6: 59–66. https://doi.org/10.1016/j.ijdrr.2013.04.002 .

Sovacool, B.K. 2008. The costs of failure: A preliminary assessment of major energy accidents, 1907–2007. Energy Policy 36 (5): 1802–1820. https://doi.org/10.1016/j.enpol.2008.01.040 .

SpringerLink. 2021. Journal Search. https://rd.springer.com/search?facet-content-type=%22Journal%22 . Accessed 11 May 2021.

Stojanovic, B., K. Hofer-Schmitz, and U. Kleb. 2020. APT datasets and attack modeling for automated detection methods: A review. Computers & Security 92: 19. https://doi.org/10.1016/j.cose.2020.101734 .

Subroto, A., and A. Apriyana. 2019. Cyber risk prediction through social media big data analytics and statistical machine learning. Journal of Big Data . https://doi.org/10.1186/s40537-019-0216-1 .

Tan, Z., A. Jamdagni, X. He, P. Nanda, R.P. Liu, and J. Hu. 2015. Detection of denial-of-service attacks based on computer vision techniques. IEEE Transactions on Computers 64 (9): 2519–2533. https://doi.org/10.1109/TC.2014.2375218 .

Tidy, J. 2021. Irish cyber-attack: Hackers bail out Irish health service for free. https://www.bbc.com/news/world-europe-57197688 . Accessed 6 May 2021.

Tuncer, T., F. Ertam, and S. Dogan. 2020. Automated malware recognition method based on local neighborhood binary pattern. Multimedia Tools and Applications 79 (37–38): 27815–27832. https://doi.org/10.1007/s11042-020-09376-6 .

Uhm, Y., and W. Pak. 2021. Service-aware two-level partitioning for machine learning-based network intrusion detection with high performance and high scalability. IEEE Access 9: 6608–6622. https://doi.org/10.1109/ACCESS.2020.3048900 .

Ulven, J.B., and G. Wangen. 2021. A systematic review of cybersecurity risks in higher education. Future Internet 13 (2): 1–40. https://doi.org/10.3390/fi13020039 .

Vaccari, I., G. Chiola, M. Aiello, M. Mongelli, and E. Cambiaso. 2020. MQTTset, a new dataset for machine learning techniques on MQTT. Sensors 20 (22): 17. https://doi.org/10.3390/s20226578 .

Valeriano, B., and R.C. Maness. 2014. The dynamics of cyber conflict between rival antagonists, 2001–11. Journal of Peace Research 51 (3): 347–360. https://doi.org/10.1177/0022343313518940 .

Varghese, J.E., and B. Muniyal. 2021. An Efficient IDS framework for DDoS attacks in SDN environment. IEEE Access 9: 69680–69699. https://doi.org/10.1109/ACCESS.2021.3078065 .

Varsha, M. V., P. Vinod, K.A. Dhanya. 2017 Identification of malicious android app using manifest and opcode features. Journal of Computer Virology and Hacking Techniques 13 (2): 125–138. https://doi.org/10.1007/s11416-016-0277-z

Velliangiri, S., and H.M. Pandey. 2020. Fuzzy-Taylor-elephant herd optimization inspired Deep Belief Network for DDoS attack detection and comparison with state-of-the-arts algorithms. Future Generation Computer Systems—the International Journal of Escience 110: 80–90. https://doi.org/10.1016/j.future.2020.03.049 .

Verma, A., and V. Ranga. 2020. Machine learning based intrusion detection systems for IoT applications. Wireless Personal Communications 111 (4): 2287–2310. https://doi.org/10.1007/s11277-019-06986-8 .

Vidros, S., C. Kolias, G. Kambourakis, and L. Akoglu. 2017. Automatic detection of online recruitment frauds: Characteristics, methods, and a public dataset. Future Internet 9 (1): 19. https://doi.org/10.3390/fi9010006 .

Vinayakumar, R., M. Alazab, K.P. Soman, P. Poornachandran, A. Al-Nemrat, and S. Venkatraman. 2019. Deep learning approach for intelligent intrusion detection system. IEEE Access 7: 41525–41550. https://doi.org/10.1109/access.2019.2895334 .

Walker-Roberts, S., M. Hammoudeh, O. Aldabbas, M. Aydin, and A. Dehghantanha. 2020. Threats on the horizon: Understanding security threats in the era of cyber-physical systems. Journal of Supercomputing 76 (4): 2643–2664. https://doi.org/10.1007/s11227-019-03028-9 .

Web of Science. 2021. Web of Science: Science Citation Index Expanded. https://clarivate.com/webofsciencegroup/solutions/webofscience-scie/ . Accessed 11 May 2021.

World Economic Forum. 2020. WEF Global Risk Report. http://www3.weforum.org/docs/WEF_Global_Risk_Report_2020.pdf . Accessed 13 May 2020.

Xin, Y., L. Kong, Z. Liu, Y. Chen, Y. Li, H. Zhu, M. Gao, H. Hou, and C. Wang. 2018. Machine learning and deep learning methods for cybersecurity. IEEE Access 6: 35365–35381. https://doi.org/10.1109/ACCESS.2018.2836950 .

Xu, C., J. Zhang, K. Chang, and C. Long. 2013. Uncovering collusive spammers in Chinese review websites. In Proceedings of the 22nd ACM international conference on Information & Knowledge Management.

Yang, J., T. Li, G. Liang, W. He, and Y. Zhao. 2019. A Simple recurrent unit model based intrusion detection system with DCGAN. IEEE Access 7: 83286–83296. https://doi.org/10.1109/ACCESS.2019.2922692 .

Yuan, B.G., J.F. Wang, D. Liu, W. Guo, P. Wu, and X.H. Bao. 2020. Byte-level malware classification based on Markov images and deep learning. Computers & Security 92: 12. https://doi.org/10.1016/j.cose.2020.101740 .

Zhang, S., X.M. Ou, and D. Caragea. 2015. Predicting cyber risks through national vulnerability database. Information Security Journal 24 (4–6): 194–206. https://doi.org/10.1080/19393555.2015.1111961 .

Zhang, Y., P. Li, and X. Wang. 2019. Intrusion detection for IoT based on improved genetic algorithm and deep belief network. IEEE Access 7: 31711–31722.

Zheng, Muwei, Hannah Robbins, Zimo Chai, Prakash Thapa, and Tyler Moore. 2018. Cybersecurity research datasets: taxonomy and empirical analysis. In 11th {USENIX} workshop on cyber security experimentation and test ({CSET} 18).

Zhou, X., W. Liang, S. Shimizu, J. Ma, and Q. Jin. 2021. Siamese neural network based few-shot learning for anomaly detection in industrial cyber-physical systems. IEEE Transactions on Industrial Informatics 17 (8): 5790–5798. https://doi.org/10.1109/TII.2020.3047675 .

Zhou, Y.Y., G. Cheng, S.Q. Jiang, and M. Dai. 2020. Building an efficient intrusion detection system based on feature selection and ensemble classifier. Computer Networks 174: 17. https://doi.org/10.1016/j.comnet.2020.107247 .

Download references

Open Access funding provided by the IReL Consortium.

Author information

Authors and affiliations.

University of Limerick, Limerick, Ireland

Frank Cremer, Barry Sheehan, Arash N. Kia, Martin Mullins & Finbarr Murphy

TH Köln University of Applied Sciences, Cologne, Germany

Michael Fortmann & Stefan Materne

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Barry Sheehan .

Ethics declarations

Conflict of interest.

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (PDF 334 kb)

Supplementary file1 (docx 418 kb), rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cremer, F., Sheehan, B., Fortmann, M. et al. Cyber risk and cybersecurity: a systematic review of data availability. Geneva Pap Risk Insur Issues Pract 47 , 698–736 (2022). https://doi.org/10.1057/s41288-022-00266-6

Download citation

Received : 15 June 2021

Accepted : 20 January 2022

Published : 17 February 2022

Issue Date : July 2022

DOI : https://doi.org/10.1057/s41288-022-00266-6

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Cyber insurance
• Systematic review
• Cybersecurity
• Find a journal
• Publish with us
• Track your research

75 Cyber Security Research Topics in 2024

Introduction to Cybersecurity Research

Cybersecurity research aims to protect computer systems, networks, and data from unauthorised access, theft, or damage. It involves studying and developing methods and techniques to identify, understand, and mitigate cyber threats and vulnerabilities. 

The field can be divided into theoretical and applied research and faces challenges such as

• Increasing complexity 
• New forms of malware 
• The growing sophistication of cyber attacks

On a daily basis, approximately 2,200 cyber attacks occur, with an average of one cyber attack happening every 39 seconds. This is the reason why researchers must stay up-to-date and collaborate with others in the field. 

In this article, let’s discuss the different cybersecurity research topics and how they will help you become an expert in the field.

Check out our  free technology courses  to get an edge over the competition.

Here are some of the latest research topics in cyber security – 

Emerging Cyber Threats and Vulnerabilities in 2024

Continual technological advancements lead to changes in cybersecurity trends, with data breaches, ransomware, and hacks becoming more prevalent. 

• Cyber Attacks and Their Countermeasures – Discuss – This research paper will discuss various cyber attacks and their corresponding countermeasures. It aims to provide insights on how organisations can better protect themselves from cyber threats.
• Is Cryptography Necessary for Cybersecurity Applications? – Explore the role of cryptography in ensuring the confidentiality, integrity, and availability of data and information in cybersecurity. It would examine the various cryptographic techniques used in cybersecurity and their effectiveness in protecting against cyber threats.

Here are some other cyber security topics that you may consider – 

• Discuss the Application of Cyber Security for Cloud-based Applications 
• Data Analytics Tools in Cybersecurity
• Malware Analysis
• What Are the Behavioural Aspects of Cyber Security? 
• Role of Cyber Security on Intelligent Transporation Systems
• How to Stop and Spot Different Types of Malware?

Check Out upGrad’s  Software Development Courses  to upskill yourself.

Machine Learning and AI in Cybersecurity Research

Machine learning and AI are research topics in cybersecurity, aiming to develop algorithms for threat detection, enhance intelligence and automate risk mitigation. However, security risks like adversarial attacks require attention.

• Using AI/ML to Analyse Cyber Threats – This cyber security research paper analyses cyber threats and could include an overview of the current state of cyber threats and how AI/ML can help with threat detection and response. The paper could also discuss the challenges and limitations of using AI/ML in cybersecurity and potential areas for further research.

Here are some other topics to consider – 

• Developing Cognitive Systems for Cyber Threat Detection and Response
• Developing Distributed Ai Systems to Enhance Cybersecurity
• Developing Deep Learning Architectures for Cyber Defence
• Exploring the Use of Computational Intelligence and Neuroscience in Enhancing Security and Privacy
• How is Cyber Security Relevant for Everyone? Discuss
• Discuss the Importance of Network Traffic Analysis
• How to Build an App to Break Ceasar Cipher

You can check out the Advanced Certificate Programme in Cyber Security course by upGrad, which will help students become experts in cyber security. 

IoT Security and Privacy

IoT security and privacy research aim to develop secure and privacy-preserving architectures, protocols, and algorithms for IoT devices, including encryption, access control, and secure communication. The challenge is to balance security with usability while addressing the risk of cyber-attacks and compromised privacy.

• Service Orchestration and Routing for IoT – It may focus on developing efficient and secure methods for managing and routing traffic between IoT devices and services. The paper may explore different approaches for optimising service orchestration. 
• Efficient Resource Management, Energy Harvesting, and Power Consumption in IoT – This paper may focus on developing strategies to improve energy use efficiency in IoT devices. This may involve investigating the use of energy harvesting technologies, optimising resource allocation and management, and exploring methods to reduce power consumption.

Here are some other cyber security project topics to consider – 

• Computation and Communication Gateways for IoT
• The Miniaturisation of Sensors, Cpus, and Networks in IoT
• Big Data Analytics in IoT
• Semantic Technologies in IoT
• Virtualisation in IoT
• Privacy, Security, Trust, Identity, and Anonymity in IoT
• Heterogeneity, Dynamics, and Scale in IoT
• Consequences of Leaving Unlocked Devices Unattended

Explore our Popular Software Engineering Courses

Blockchain security: research challenges and opportunities.

Blockchain security research aims to develop secure and decentralised architectures, consensus algorithms, and privacy-preserving techniques while addressing challenges such as smart contract security and consensus manipulation. Opportunities include transparent supply chain management and decentralised identity management.

• Advanced Cryptographic Technologies in the Blockchain – Explore the latest advancements and emerging trends in cryptographic techniques used in blockchain-based systems. It could also analyse the security and privacy implications of these technologies and discuss their potential impact. 
• Applications of Smart Contracts in Blockchain – Explore the various use cases and potential benefits of using smart contracts to automate and secure business processes. It could also examine the challenges and limitations of smart contracts and propose potential solutions for these issues.

Here are some other topics – 

• Ensuring Data Consistency, Transparency, and Privacy in the Blockchain
• Emerging Blockchain Models for Digital Currencies
• Blockchain for Advanced Information Governance Models
• The Role of Blockchain in Future Wireless Mobile Networks
• Law and Regulation Issues in the Blockchain
• Transaction Processing and Modification in the Blockchain
• Collaboration of Big Data With Blockchain Networks

Cloud Security: Trends and Innovations in Research

Cloud security research aims to develop innovative techniques and technologies for securing cloud computing environments, including threat detection with AI, SECaaS, encryption and access control, secure backup and disaster recovery, container security, and blockchain-based solutions. The goal is to ensure the security, privacy, and integrity of cloud-based data and applications for organisations.

• Posture Management in Cloud Security – Discuss the importance of identifying and addressing vulnerabilities in cloud-based systems and strategies for maintaining a secure posture over time. This could include topics such as threat modelling, risk assessment, access control, and continuous monitoring.
• Are Cloud Services 100% Secure?
• What is the Importance of Cloud Security?
• Cloud Security Service to Identify Unauthorised User Behaviour
• Preventing Theft-of-service Attacks and Ensuring Cloud Security on Virtual Machines
• Security Requirements for Cloud Computing
• Privacy and Security of Cloud Computing

Explore Our Software Development Free Courses

Cybercrime investigations and forensics.

Cybercrime investigations and forensics involve analysing digital evidence to identify and prosecute cybercriminals, including developing new data recovery, analysis, and preservation techniques. Research also focuses on identifying cybercriminals and improving legal and regulatory frameworks for prosecuting cybercrime.

• Black Hat and White Hat Hacking: Comparison and Contrast – Explore the similarities and differences between these two approaches to hacking. It would examine the motivations and methods of both types of hackers and their impact on cybersecurity.
• Legal Requirements for Computer Forensics Laboratories
• Wireless Hacking Techniques: Emerging Technologies and Mitigation Strategies
• Cyber Crime: Current Issues and Threats
• Computer Forensics in Law Enforcement: Importance and Challenges
• Basic Procedures for Computer Forensics and Investigations
• Digital Forensic Examination of Counterfeit Documents: Techniques and Tools
• Cybersecurity and Cybercrime: Understanding the Nature and Scope

An integral part of cybercrime investigation is to learn software development. Become experts in this field with the help of upGrad’s Executive Post Graduate Programme in Software Development – Specialisation in Full Stack Development . 

Cybersecurity Policy and Regulations

Cybersecurity policy and regulations research aims to develop laws, regulations, and guidelines to ensure the security and privacy of digital systems and data, including addressing gaps in existing policies, promoting international cooperation, and developing standards and best practices for cybersecurity. The goal is to protect digital systems and data while promoting innovation and growth in the digital economy.

• The Ethicality of Government Access to Citizens’ Data – Explore the ethical considerations surrounding government access to citizens’ data for surveillance and security purposes, analysing the potential risks and benefits and the legal and social implications of such access. 
• The Moral Permissibility of Using Music Streaming Services – Explore the ethical implications of using music streaming services, examining issues such as intellectual property rights, artist compensation, and the environmental impact of streaming. 
• Real Name Requirements on Internet Forums
• Restrictions to Prevent Domain Speculation
• Regulating Adult Content Visibility on the Internet
• Justification for Illegal Downloading
• Adapting Law Enforcement to Online Technologies
• Balancing Data Privacy With Convenience and Centralisation
• Understanding the Nature and Dangers of Cyber Terrorism

Human Factors in Cybersecurity

Human factors in cybersecurity research study how human behaviour impacts cybersecurity, including designing interfaces, developing security training, addressing user error and negligence, and examining cybersecurity’s social and cultural aspects. The goal is to improve security by mitigating human-related security risks.

• Review the Human Factors in Cybersecurity –  It explores various human factors such as awareness, behaviour, training, and culture and their influence on cybersecurity, offering insights and recommendations for improving cybersecurity outcomes.
• Integrating Human Factors in Cybersecurity for Better Risk Management
• Address the Human Factors in Cybersecurity Leadership
• Human Factors in IoT Security
• Internal Vulnerabilities: the Human Factor in It Security
• Cyber Security Human Factors – the Ultimate List of Statistics and Data

In-Demand Software Development Skills

Cybersecurity education and awareness.

Cybersecurity education and awareness aims to educate individuals and organisations about potential cybersecurity threats and best practices to prevent cyber attacks. It involves promoting safe online behaviour, training on cybersecurity protocols, and raising awareness about emerging cyber threats.

• Identifying Phishing Attacks – This research paper explores various techniques and tools to identify and prevent phishing attacks, which are common types of cyber attacks that rely on social engineering tactics to trick victims into divulging sensitive information or installing malware on their devices.
• Risks of Password Reuse for Personal and Professional Accounts – Investigate the risks associated with reusing the same password across different personal and professional accounts, such as the possibility of credential stuffing attacks and the impact of compromised accounts on organisational security. 
• Effective Defence Against Ransomware
• Information Access Management: Privilege and Need-to-know Access
• Protecting Sensitive Data on Removable Media
• Recognising Social Engineering Attacks
• Preventing Unauthorised Access to Secure Areas: Detecting Piggybacking and Tailgating
• E-mail Attack and Its Characteristics
• Safe Wifi Practice: Understanding VPN

With the increasing use of digital systems and networks, avoiding potential cyber-attacks is more important than ever. The 75 research topics outlined in this list offer a glimpse into the different dimensions of this important field. By focusing on these areas, researchers can make significant contributions to enhancing the security and safety of individuals, organisations, and society as a whole.

upGrad’s Master of Science in Computer Science program is one of the top courses students can complete to become experts in the field of tech and cyber security. The program covers topics such as Java Programming and other forms of software engineering which will help students understand the latest technologies and techniques used in cyber security. 

The program also includes hands-on projects and case studies to ensure students have practical experience in applying these concepts. Graduates will be well-equipped to take on challenging roles in the rapidly growing field of cyber security.

Pavan Vadapalli

Something went wrong

Our Popular Software Engineering Courses

Our Trending Software Engineering Courses

• Master of Science in Computer Science from LJMU
• Executive PG Program in Software Development Specialisation in Full Stack Development from IIIT-B
• Advanced Certificate Programme in Cyber Security from IIITB
• Full Stack Software Development Bootcamp
• Software Engineering Bootcamp from upGrad

Popular Software Development Skills

• React Courses
• Javascript Courses
• Core Java Courses
• Data Structures Courses
• ReactJS Courses
• NodeJS Courses
• Blockchain Courses
• SQL Courses
• Full Stack Development Courses
• Big Data Courses
• Devops Courses
• NFT Courses
• Cyber Security Courses
• Cloud Computing Courses
• Database Design Courses
• Crypto Courses
• Python Courses

Frequently Asked Questions (FAQs)

Artificial intelligence (AI) has proved to be an effective tool in cyber defence. AI is anticipated to gain even more prominence in 2024, mainly in monitoring, resource and threat analysis, and quick response capabilities.

One area of focus is the development of secure quantum and space communications to address the increasing use of quantum technologies and space travel. Another area of research is improving data privacy.

The approach to cybersecurity is expected to change from defending against attacks to acknowledging and managing ongoing cyber risks. The focus will be on improving resilience and recovering from potential cyber incidents.

Related Programs View All

Certification

40 Hrs Live, Expert-Led Sessions

2 High-Quality Practice Exams

View Program

Executive PG Program

IIIT-B Alumni Status

Master's Degree

40000+ Enrolled Learners

Job Assistance

32-Hr Training by Dustin Brimberry

Question Bank with 300+ Practice Qs

45 Hrs Live Expert-Led Training

Microsoft-Approved Curriculum

159+ Hours of Live Sessions

126+ Hours of Live Sessions

Fully Online

13+ Hrs Instructor-Led Sessions

Live Doubt-Solving Sessions

2 Unique Specialisations

300+ Hiring Partners

20+ Hrs Instructor-Led Sessions

16 Hrs Live Expert-Led Training

CLF-C02 Exam Prep Support

24 Hrs Live Expert-Led Training

4 Real-World Capstone Projects

17+ Hrs Instructor-Led Training

3 Real-World Capstone Projects

289 Hours of Self-Paced Learning

10+ Capstone Projects

490+ Hours Self-Paced Learning

4 Real-World Projects

690+ Hours Self-Paced Learning

Cloud Labs-Enabled Learning

288 Hours Self-Paced Learning

9 Capstone Projects

40 Hrs Live Expert-Led Sessions

2 Mock Exams, 9 Assessments

Executive PG Certification

GenAI integrated curriculum

Job Prep Support

Instructor-Led Sessions

Hands-on UI/UX

16 Hrs Live Expert-Led Sessions

12 Hrs Hand-On Practice

30+ Hrs Live Expert-Led Sessions

24+ Hrs Hands-On with Open Stack

2 Days Live, Expert-Led Sessions

34+ Hrs Instructor-Led Sessions

10 Real-World Live Projects

24 Hrs Live Expert-Led Sessions

16 Hrs Hand-On Practice

8 Hrs Instructor-Led Training

Case-Study Based Discussions

40 Hrs Instructor-Led Sessions

Hands-On Practice, Exam Support

24-Hrs Live Expert-Led Sessions

Regular Doubt-Clearing Sessions

Extensive Exam Prep Support

6 Hrs Live Expert-Led Sessions

440+ Hours Self-Paced Learning

400 Hours of Cloud Labs

15-Hrs Live Expert-Led Sessions

32 Hrs Live Expert-Led Sessions

28 Hrs Hand-On Practice

Mentorship by Industry Experts

24 Hrs Live Trainer-Led Sessions

Mentorship by Certified Trainers

GenAI Integrated Curriculum

Full Access to Digital Resources

16 Hrs Live Instructor-Led Sessions

80+ Hrs Hands-On with Cloud Labs

160+ Hours Live Instructor-Led Sessions

Hackathons and Mock Interviews

31+ Hrs Instructor-Led Sessions

120+ Hrs of Cloud Labs Access

35+ Hrs Instructor-Led Sessions

6 Real-World Live Projects

24+ Hrs Instructor-Led Training

Self-Paced Course by Nikolai Schuler

Access Digital Resources Library

300+ Hrs Live Expert-Led Training

90 Hrs Doubt Clearing Sessions

56 Hours Instructor-Led Sessions

78 Hrs Live Expert-Led Sessions

22 Hrs Live, Expert-Led Sessions

CISA Job Practice Exams

Explore Free Courses

Learn more about the education system, top universities, entrance tests, course information, and employment opportunities in Canada through this course.

Advance your career in the field of marketing with Industry relevant free courses

Build your foundation in one of the hottest industry of the 21st century

Master industry-relevant skills that are required to become a leader and drive organizational success

Build essential technical skills to move forward in your career in these evolving times

Get insights from industry leaders and career counselors and learn how to stay ahead in your career

Kickstart your career in law by building a solid foundation with these relevant free courses.

Stay ahead of the curve and upskill yourself on Generative AI and ChatGPT

Build your confidence by learning essential soft skills to help you become an Industry ready professional.

Learn more about the education system, top universities, entrance tests, course information, and employment opportunities in USA through this course.

Suggested Tutorials

Explore Python programming with this concise tutorial, covering basics to advanced concepts for beginners and enthusiasts alike.

Introduction to C Programming, Learn all the C programming language concepts in this tutorial.

Suggested Blogs

12 Apr 2024

by Rohan Vats

05 Mar 2024

by Prateek Singh

29 Feb 2024

by venkatesh Rajanala

by Harish K

by Geetika Mathur

by spandita hati

• Write my thesis
• Thesis writers
• Buy thesis papers
• Bachelor thesis
• Master's thesis
• Thesis editing services
• Thesis proofreading services
• Buy a thesis online
• Write my dissertation
• Dissertation proposal help
• Pay for dissertation
• Custom dissertation
• Dissertation help online
• Buy dissertation online
• Cheap dissertation
• Dissertation editing services
• Write my research paper
• Buy research paper online
• Pay for research paper
• Research paper help
• Order research paper
• Custom research paper
• Cheap research paper
• Research papers for sale
• Thesis subjects
• How It Works

50 Great Cybersecurity Research Paper Topics

Students are required to write papers and essays on cyber security topics when pursuing programs in cyber security disciplines. These topics are technical and they require learners to inherently understand this subject. What’s more, students should have impeccable research and writing skills.

Additionally, students should choose cyber security topics to write their papers and essays carefully. As a science field, cyber security is developing rapidly and constantly. As such, learners can always find interesting topics to write papers and essays about.

Pick Cyber Security Topics From Our List

Software and computer administration cyber security topics.

• Cyber Security Research Paper Topics on Data Protection
• Cyber Security Awareness Topics

Network Security Topic Ideas

• Current and Interesting Topics in Cyber Security

Nevertheless, selecting cybersecurity topics for research shouldn’t be a rushed process. That’s because the chosen topics will influence the experience of students while writing and the grades they will score. Therefore, learners should focus on choosing topics that they will be comfortable researching and writing about.

If you’re having a hard time choosing the topics to research and write about, here are categories of some of the best cybersecurity paper topics that you can consider. We also advise you to check out capstone project topics .

The cyber security of a company can be compromised in many ways when it comes to software and computer administration. As such, software and computer administration is a great sources of cybersecurity research paper topics. Here are some of the best topics in this category.

• Evaluation of the operation of antimalware in preventing cyber attacks
• How does virus encryption work
• Is countering malware difficult because of the fast evolution of technology?
• Why should companies train their staff on cyber security?
• Why should people worry about identity theft?
• How important are software updates when it comes to cyber security?
• What causes cyber crimes?
• What are the major threats to the cyber security of social media users?
• What are the most effective methods of preventing phishing?
• What is the major threat to cyber security today and why?

These topics address issues that affect anybody or any organization that uses a computer or any device to access the internet and exchange information. As such, most people, including teachers and professors, will be impressed by papers and essays written about them.

CyberSecurity Research Paper Topics on Data Protection

Individuals and companies send and receive a lot of data every day. As such, this category has some of the best cybersecurity topics for presentation. That’s because they address issues that affect many people and organizations. Here are some of the best information security topics to consider when writing papers and essays or preparing a presentation.

• The best security measures for protecting your data
• How third-party applications can be used to access and acquire data without permission
• How to prevent the loss of data from a computer
• Can biometrics be used to prevent unauthorized data access?
• Can you protect yourself from cyber crimes by keeping personal data private?
• What should you do in case of a data breach?
• How can you secure your data with a 2-steps authentication process?
• How can public Wi-Fi or the internet be used to steal personal data?
• What information can be accessed by unauthorized persons if they hack an account?
• Can software updates help in protecting personal data?

Every computer or internet user wants to be sure that their data is safe and protected. Papers and essays that are written on these topics address issues of data protection. As such, many people will find them worth reading.

CyberSecurity Awareness Research Paper Topics

The best cyber security topics for research papers do more than just address a single issue. They also inform the readers. Here are some of the best cyber security topics for research papers that also focus on creating awareness.

• What is reverse engineering?
• How efficient are RFID security systems?
• How does the dark web propagate organized cyber crimes?
• How can steganalysis be applied?
• Analyze the best authorization infrastructures today
• How important is computer forensics in the current digital era?
• What strategies have been proven effective in preventing cyber-attacks?
• Which forensic tools are the best when it comes to detecting cyber threats?
• Can changing the password regularly help in predicting a cyber attack?
• How can you tell that you’re at risk of online identity theft?

Many people are not aware of many things that affect their cyber security. These topics are relevant because they enhance the awareness of the internet and computer users.

Most organizations today have networked systems that enhance their operations. Unfortunately, criminals have learned to target those networked systems with their criminal activities. As such, students can address some of these issues with their cyber security thesis topics. Here are interesting topics that learners can research and write about in this category.

• Evaluation of the cyber security legal framework in the U.S
• Analysis of the most difficult aspect of the administration of cyber security
• How can the possibilities of multiple threats be managed effectively?
• How does data backup help when it comes to cyber security?
• How effective is two-factor authentication?
• How should a company respond to hacking in its system?
• Which are the best cyber security protection approaches for a multinational company?
• What are the pros and cons of unified user profiles?
• What are the most important components of effective data governance?
• What motivates individuals to commit cybercrimes?

These computer security topics can be used to write papers and essays for college or even commissioned by organizations and used for presentation purposes.

Current and Interesting Topics in CyberSecurity

Some computer security research topics seek to address issues that affect society at the moment. Here are examples of such topics.

• How phishing is evolving and getting more sophisticated
• Explain the evolution of Ransomware strategies
• Explain how the cryptocurrency movement affects cybersecurity
• Cyber-Physical Attacks: How do they work?
• What are state-sponsored attacks and how do they affect cyber security at a global level?
• Discuss cyber security risks when it comes to third-party vendor relationships
• How digital advertisements are being used to collect user characteristics
• How can a person sync all their devices while ensuring their protection
• Why it’s advisable to avoid downloading files from sites that are not trusted
• Why consumers should read the terms and conditions of software before they decide to install it

Such technology security topics are trendy because they address issues that affect most people in modern society. Nevertheless, students should conduct extensive research to draft solid papers and essays on these topics.

This cyber security topic list is not exhaustive. You can contact our thesis writers if you need more ideas or help. Students have many topics to consider depending on their academic programs, interests, and instructions provided by educators or professors. Nevertheless, students should focus on choosing topics that will enable them to come up with informative and comprehensive papers. Thus, every student should choose an information security topic for which they can find relevant and supporting data.

Leave a Reply Cancel reply

A List of 181 Hot Cyber Security Topics for Research [2024]

Your computer stores your memories, contacts, and study-related materials. It’s probably one of your most valuable items. But how often do you think about its safety?

Our specialists will write a custom essay specially for you!

Cyber security is something that can help you with this. Simply put, it prevents digital attacks so that no one can access your data. Do you want to write a research paper related to the modern challenges of cyberspace? This article has all you need. In here, you’ll find:

• An overview of cyber security’s research areas.
• A selection of compelling cyber security research topics.

And don’t hesitate to contact our custom writing team in case you need any assistance!

• 🔝 Top 10 Topics
• ✅ Research Areas
• ⭐ Top 10 Cybersecurity Topics
• 🔒 Technology Security Topics
• 🖥️ Cybercrime Topics
• ⚖️ Cyber Law & Ethics Topics

🔍 References

🔝 top 10 cyber security topics.

• How does malware work?
• The principle of zero trust access
• 3 phases of application security
• Should removable media be encrypted?
• The importance of network security
• The importance of end-user education
• Cloud security posture management
• Do biometrics ensure security of IPhones?
• Can strong passwords protect information?
• Is security in critical infrastructure important?

✅ Cyber Security Topics & Research Areas

Cyber security is a vast, constantly evolving field. Its research takes place in many areas. Among them are:

• Safe quantum and space communications . Progress in quantum technologies and space travel calls for extra layers of protection.
• Data privacy. If someone’s personal information falls into the wrong hands, the consequences can be dire. That’s why research in this area focuses on encryption techniques.
• (Inter)national cyberethics, criminology, and law. This branch analyzes how international legal frameworks work online.
• AI and IoT security . We spend more and more of our daily lives online. Additionally, our reliance on AI increases. This scientific field strives to ensure a safe continuation of this path.

As you can see, cyber security extends in various exciting directions that you can explore. Naturally, every paper needs a cover page. We know that it’s one of the more annoying parts, so it’s not a bad thing to use a title page generator for your research paper . Now, let’s move on to our cyber topics list.

⭐ Top 10 Cybersecurity Topics 2024

• Is removable media a threat?
• Blockchain security vulnerabilities
• Why should you avoid public Wi-Fi?
• How to prevent phishing attacks
• Physical security measures in banks
• Security breaches of remote working
• How does two-factor authentication work?
• How to prevent social engineering attacks
• Cybersecurity standards for automotive
• Privacy settings of social media accounts

🔒 Computer Security Topics to Research

Safe computer and network usage is crucial. It concerns not only business but also individuals. Security programs and systems ensure this protection. Explore them with one of our topics:

Just in 1 hour! We will write you a plagiarism-free paper in hardly more than 1 hour

• How do companies avoid sending out confidential information? Sending an email to the wrong person has happened to the best of us. But what happens if the message’s contents were classified? For your paper, you can find out what technologies can prevent such slip-ups. 
• What are the best ways to detect malicious activity? Any organization’s website gets plenty of daily traffic. People log in, browse, and interact with each other. Among all of them, it might be easy for an intruder to slip in.  
• Internet censorship: classified information leaks . China takes internet censorship to the next level. Its comprehensive protection policies gave the system the nickname Great Firewall of China . Discuss this technology in your essay.
• Encrypted viruses as the plague of the century. Antivirus programs are installed on almost every computer. They prevent malicious code from tampering with your data. In your paper, you can conduct a comparison of several such programs. 
• What are the pros and cons of various cryptographic methods? Data privacy is becoming more and more critical. That’s why leading messaging services frequently advertise with their encryption technologies.  
• What makes blockchain secure? This technique allows anonymity and decentralization when working with cryptocurrencies. How does it work? What risks are associated with it? 
• What are the advantages of SIEM ? Security Incident and Event Management helps organizations detect and handle security threats. Your essay can focus on its relevance for businesses. 
• What are the signs of phishing attempts?
• Discuss unified cyber security standards in healthcare. 
• Compare and contrast various forms of data extraction techniques.
• What do computers need protocols for?
• Debate the significance of frequent system updates for data security .
• What methods does HTTPS use that make it more secure than HTTP?
• The role of prime numbers in cryptography .
• What are public key certificates, and why are they useful? 
• What does a VPN do?
• Are wireless internet connections less secure than LAN ones? If so, why? 
• How do authentication processes work?
• What can you do with IP addresses?
• Explain the technology of unlocking your phone via facial recognition vs. your fingerprint.
• How do you prevent intrusion attempts in networks ?
• What makes Telnet vulnerable?
• What are the phases of a Trojan horse attack?
• Compare the encryption technologies of various social networks. 
• Asymmetric vs. symmetric algorithms.
• How can a person reach maximum security in the computer networking world ?
• Discuss autoencoders and reveal how they work.

💾 Information Security Topics to Research

Information security’s goal is to protect the transmission and storage of data. On top of that, network security topics are at the forefront of infosec research. If you’re looking for inspiration on the subject, check out these ideas.

• What are the mechanics of password protection? Passwords are a simple tool to ensure confidentiality. What do users and developers need to keep in mind when handling passwords? 
• What are the safest ways to ensure data integrity ? Everybody wants their data to be intact. Accidental or malicious modifications of data can have dire consequences for organizations and individuals. Explore ways to avoid it.
• How can one establish non-repudiation? Non-repudiation proves the validity of your data. It’s essential in legal cases and cyber security .
• How did the advent of these new technologies impact information security ? Mobile networks have changed the way we access information. On a smartphone , everything is permanently available at your fingertips. What adverse consequences did these technologies bring?
• How do big corporations ensure that their database environment stays conflict-free? We expect our computers to always run fast and without errors. For institutions such as hospitals, a smooth workflow is vital. Discuss how it can be achieved.
• Describe solid access control methods for organizations. In a company, employees need access to different things. This means that not everyone should have an admin account. How should we control access to information ?
• Medical device cyber security. For maximum safety, it’s best to employ several measures. Protection on the hard- and software side is just a part of it. What are some other means of security? 
• Write an argumentative essay on why a career in information security doesn’t require a degree. 
• Pros and cons of various infosec certificates. 
• Cybersecurity in cruise ship industry
• The influence of remote work on a businesses’ infosec network .
• What should everyone be aware of when it comes to safeguarding private information?
• Select a company and calculate how much budget they should allocate on cyber security.
• What are the dangers of public Wi-Fi networks? 
• How secure are cloud services ?
• Apple vs. Microsoft : whose systems offer better security?
• Why is it important to remove a USB flash drive safely?
• Is it possible to create an unguessable password?
• Intranet security: best practices. 
• Does the use of biometrics increase security? 
• Face recognition vs. a simple code: what are the safest locking options for smartphones ?
• How do you recover data from a broken hard drive?
• Discuss the functions and risks of cookies and cache files.
• Online privacy regulations in the US and China. 
• Physical components of InfoSec. 
• Debate security concerns regarding electronic health records .
• What are unified user profiles, and what makes them potentially risky?

🖥️ Cybercrime Topics for a Research Paper

Knowledge is one of today’s most valuable assets. Because of this, cybercrimes usually target the extraction of information. This practice can have devastating effects. Do you want to learn more about the virtual world’s dark side? This section is for you.

• Give an overview of the various types of cybercrimes today . Cybercriminals are becoming more and more inventive. It’s not easy to keep up with the new threats appearing every day. What threats are currently the most prominent? 
• How does cryptojacking work, and why is it problematic? Cryptocurrency’s value explosion has made people greedy. Countries such as Iceland have become a haven for datamining. Explore these issues in your essay.
• Analyze the success rate of email frauds. You’ve probably seen irrelevant ads in your spam folder before. They often sound so silly it’s hard to believe they work. Yet, unfortunately, many people become victims of such scams. 
• How did the WannaCry malware work? WannaCry was ransomware that caused global trouble in 2017. It led to financial losses in the billions. What made it so dangerous and hard to stop?
• Give famous examples of cybercrimes that targeted people instead of money . Not all cybercrimes want to generate profit. Sometimes, the reasons are political or personal. Explore several instances of such crimes in your essay. How did they pan out?

• Analyze the implications of the Cyberpunk 2077 leak. The game’s bugs and issues made many people angry. Shortly after its flop, hackers released developer CD Projekt Red’s source codes. What far-reaching consequences could this have?
• Why do hackers commit identity theft? Social media has made it easy to steal identities . Many like to display their lives online. In your paper, research what happens to the victims of identity thefts. 
• Should governments punish cybercrimes like real-life crimes?
• How does ransomware work?
• Describe the phases of a DDoS attack.
• What cybercrime cases led to changes in the legislature? 
• Track the evolution of online scams.
• Online grooming: how to protect children from predators. 
• Are cybercrimes “gateway crimes” that lead to real-life misbehavior?
• What are man-in-the-middle attacks?
• Big data and the rise of internet crimes.
• Are cybercrimes more dangerous to society than they are to corporations?
• Is the internet increasing the likelihood of adolescents engaging in illegal activities?
• Do the downsides of cyberlife outweigh its positives?
• Is constantly checking your crush’s Facebook page cyberstalking?
• How do you recognize your online date is a scam?
• Describe what happens during a Brute Force attack.
• What’s the difference between pharming and phishing?
• The Lehman Bank cybercrimes.
• Should the punishments for cybercriminals be harsher than they are now?
• Compare various types of fraud methods .
• How do you mitigate a denial-of-service attack? 

🕵️ Topics for a Research Paper on Hacking

Blinking screens and flashing lines of code: the movie industry makes hacking look fascinating. But what actually happens when someone breaks into another person’s computer’s system? Write a paper about it and find out! The following prompts allow you to dive deeper into the subject.

• Is it vital to keep shutting down online movie streaming sites? Many websites offer free movie streaming. If one of their domains gets closed down, they just open another one. Are they a threat to the industry that must be stopped? Or should cyber law enforcement rather focus on more serious crimes?
• Explore the ethical side of whistleblowing. WikiLeaks is a platform for whistleblowers. Its founder, Julian Assange, has been under arrest for a long time. Should whistleblowing be a crime? Why or why not?
• How did Kevin Mitnick’s actions contribute to the American cyber legislature? Mitnick was one of the US’s first most notorious hackers. He claimed to have broken into NORAD’s system. What were the consequences?
• Examine how GhostNet operates. GhostNet is a large organization attacking governments. Its discovery in 2009 led to a major scandal.
• Describe how an SQL injection attack unfolds. Injection attacks target SQL databases and libraries. This way, hackers gain unauthorized access to data.  
• What political consequences did the attack on The Interview imply? In 2014, hackers threatened to attack theaters that showed The Interview . As a result, Sony only showed the movie online and in limited releases.
• Write about cross-site request forgery attacks. Every website tells you that logging out is a crucial step. But what can happen if you don’t do it?
• What is “Anonymous,” and what do they do?
• Is it permissible to hack a system to raise awareness of its vulnerabilities?
• Investigate the origins of the hacking culture .
• How did industrial espionage evolve into hacking?
• Is piracy destroying the music and movie industries ?
• Explain the term “cyberwarfare.”
• Contrast different types of hacking. 
• Connections between political protests and hacking. 
• Is it possible to create an encryption that can’t be hacked?
• The role of hackers in modern warfare .
• Can hacking be ethical?
• Who or what are white hat hackers ?
• Discuss what various types of hackers do.
• Is jailbreaking a crime? 
• How does hacking a phone differ from hacking a computer?
• Is hacking your personal home devices problematic?
• What is clickjacking?
• Why would hackers target newspapers ?
• Examine the consequences society would have to bear if a hacker targeted the state.
• Compare and analyze different hacking collectives.

⚖️ Topics on Cyber Law & Ethics to Look Into

Virtual life needs rules just like the real one does. The online world brings a different set of values and issues to the table. And, naturally, cyberlife has a legal framework. That’s where researching cyber law and ethics comes into play.

• Is it ethical that governments can always access their citizens’ data? In some countries, online platforms for personal information are standard. From medical exams to debts, everything is available with a click. The system is inarguably convenient. But what about its downsides? 
• Is it still morally permissible to use Spotify ? Spotify has made listening to music more accessible than ever. However, artists only receive a tiny fraction of the company’s profits. Discuss the implications of this fact.
• Should internet forums require users to display their real names? Online harassment is a widespread problem. Nicknames hide the identities of ordinary users as well as perpetrators. Can the mandatory use of real names change the situation? 
• Analyze online gaming behavior from a psychological standpoint. If one wants to play online games, one needs to have a thick skin. The community can be harsh. You can dedicate your paper to exploring these behaviors. Or you might want to ponder what game publishers can do to reduce hate speech.
• What type of restrictions should sellers implement to prevent domain speculation? Some people buy domains hoping that they will sell them later for more money. This practice makes registering a new website trickier.  
• Does the internet need regulations to make adult content less visible? Every computer without parental control can access pornographic websites. Most of them don’t require registration. Their contents can be disturbing, and their ads can appear anywhere. What can be done about it? 
• What are cyber laws still missing in America? The US has established many laws to regulate internet usage. Select the most significant ones and explain their relevance.
• Why should cyber ethics be different from real-world norms?
• Are there instances in which illegal downloading is justified?
• The rule of law in real life vs. in cyberspace.
• Does the internet need a government?
• What is cyber terrorism, and what makes it dangerous?
• Who is responsible for online misbehavior?
• How binding are netiquettes?
• What did the implementation of the GDPR change?
• Compare and contrast Indian vs. Venezuelan internet regulations.
• What does the CLOUD entail?
• How should law enforcement adapt to online technologies?
• AI applications : ethical limits and possibilities.
• Discuss trending topics in cyber law of the past ten years.
• Should schools teach online etiquette?
• Does internet anonymity bring out the worst in people?
• Is data privacy more important than convenience and centralization?
• Debate whether bitcoins could become the currency of the future. 
• How can online consumers protect themselves from fraud? 
• Is buying from websites like eBay and Craigslist more ethical than buying from other online marketplaces?
• Present RSF’s Minecraft library and discuss its moral implications.

🖱️ Cyberbullying Topics for Essays and Papers

On the web, everyone can remain anonymous. With this added comfort, bullying rises to another level. It’s a serious issue that’s getting more and more problematic. Cyber security measures can alleviate the burden. Do you want to address the problem? Have a look at our cyberbullying topics below.

Receive a plagiarism-free paper tailored to your instructions. Cut 15% off your first order!

• Cyberbullying prevention in online learning environments . Online classes increase the possibility of cyberbullying. What can teachers do to watch out for their students?
• What makes online emotional abuse particularly difficult to bear? Bullying doesn’t necessarily have to be physical to hurt. Statistics show increased suicide rates among students who were harassed online. Explore the reasons behind this phenomenon. 
• How can victims of identity theft reclaim their lives? Identity theft leads not only to mental distress. Thieves also have access to credit card information and other essential assets.
• What are the best methods to stay safe online? When surfing the internet, one always has to be on one’s toes. Avoiding harassment and bullying is a particularly challenging task.  
• How can parents monitor their children’s behavior on the web? Children are particularly vulnerable online. They might enter dangerous online relationships with strangers if they feel lonely. They are also more susceptible to scams. What can parents do to protect them?
• Cyberbullying among university students. Online abuse in such websites is very common. Everyone can be a potential target, regardless of age or gender. Discuss whether the structure of social networks helps to spread cyberbullying.
• What societal factors contribute to online bullying? Not everyone who uses the internet becomes an abuser. It’s possible to establish several psychological characteristics of cyberbullies. Explore them in your paper.
• Define how cyberbullying differs from in-person harassment. 
• Establish a link between feminism and the fight against cyberstalking .
• The emotional consequences of physical vs. verbal abuse.
• The effects of cyberbullying and academics.
• Short vs. long-term mental health effects of internet bullying .
• What are the most widespread means of cyberbullying? 
• Should people who want to play video games online get over the fact that the community is toxic?
• Is defending the freedom of speech more important than preventing the spread of hate speech?
• Reasons and consequences of Amanda Todd’s suicide.
• The dangers of pro-ana/-mia communities for adolescents.
• What are effective strategies to cope with online harassment ?
• Would cyber communism decrease bullying? 
• How enhanced cyber security measures can help reduce abuse.
• The importance of parental control mechanisms on children’s computers.
• Traditional vs. cyberbullying in children.
• Do image-heavy websites such as Tumblr and Instagram affect one’s mental state similarly to active abuse?
• What kind of people does cyber abuse affect the most, and why?
• Analyze how the stalker uses the internet in Netflix’s series You .
• Catfishing: effects and solutions.

Thanks for reading through our article. If you found it helpful, consider sharing it with your friends. We wish you good luck with your project!

Further reading:

• 220 Best Science and Technology Essay Topics to Write About
• 204 Research Topics on Technology & Computer Science
• A List of 580 Interesting Research Topics [2024 Edition]
• A List of 179 Problem Solution Essay Topics & Questions
• 193 Interesting Proposal Essay Topics and Ideas
• 226 Research Topics on Criminal Justice & Criminology
• What Is Cybersecurity?: Cisco
• Cyber Security: Research Areas: The University of Queensland, Australia
• Cybersecurity: National Institute of Standards and Technology
• What Is Information Security?: CSO Online
• Articles on Cyber Ethics: The Conversation
• What Is Cybercrime?: Kaspersky
• Types of Cybercrime and How to Protect Yourself Against Them: Security Traits
• Hacking: Computing: Encyclopedia Britannica
• Hacking News: Science Daily
• Cyberbullying and Cybersecurity: How Are They Connected?: AT&T
• Cyberbullying: What Is It and How to Stop It: UNICEF
• Current Awareness: Cyberlaw Decoded: Florida State University
• Share to Facebook
• Share to Twitter
• Share to LinkedIn
• Share to email

Have you ever wondered why everyone has a unique set of character traits? What is the connection between brain function and people’s behavior? How do we memorize things or make decisions? These are quite intriguing and puzzling questions, right? A science that will answer them is psychology. It’s a multi-faceted...

Participating in a student exchange program is a perfect opportunity to visit different countries during your college years. You can discover more about other cultures and learn a new language or two. If you have a chance to take part in such a foreign exchange, don’t miss it. Keep in...

How can you define America? If you’ve ever asked yourself this question, studying US history will help you find the answer. This article will help you dive deeper into this versatile subject. Here, you will find: Early and modern US history topics to write about. We’ve also got topics for...

Are you looking for perfect feminist topics? Then you’ve come to the right place. With our help, you can be sure to craft a great essay. Here, you can find feminist topics for discussion, feminism research topics and other ideas and questions for students. Some people think all feminists hate...

If you have an assignment in politics, look no further—this article will help you ace your paper. Here, you will find a list of unique political topics to write about compiled by our custom writing team. But that’s not all of it! Keep reading if you want to: Now, without further ado, let’s get started! Below, you’ll find political topics and questions for your task. 🔝 Top 10 Political...

It’s not a secret that our health largely depends on nutrition. A balanced and wholesome diet improves our immune system. It lowers the risk of getting sick and makes us more productive. But if we don’t eat right, our overall well-being and performance worsen. You see, nutrition topics are more...

A presentation is a speech in which you explain a topic to an audience. It usually includes visuals done in a program such as PowerPoint. Teachers in schools and in colleges love to assign presentations for various reasons: In this article, you’ll find a list of 625 presentation topics in...

In modern societies, people do everything to live peacefully. Still, tensions often arise. We call them social issues when they start negatively impacting a specific group of people. Poverty, discrimination, and addiction are examples of such problems. We need to confront them to ensure equal treatment for everyone.

There are many ways to define popular culture. Here’s one of them: pop culture includes mainstream preferences in society within a specific time frame. It covers fashion, music, language, and even food. Pop culture is always evolving, engaging in new trends, and leaving the old ones behind.

Sociology is a study that focuses on people’s interactions. It looks at structures and changes in social life. Any situation involving people can become a topic of sociology. This article is designed to help high school and college students with sociology assignments. Whether you’re writing an essay, creating a presentation,...

Controversial issues are the ones that evoke a variety of opinions. They often cause heated debates. And, as you can guess, controversial research topics are not easy to handle. Luckily, we’ve got you covered. This article will: We gathered controversial topics for research paper on medical, science, education, and other...

Plates break when you drop them. Glasses help you see better. Have you ever wondered why? Physics has the answer. It studies the observable as well as invisible aspects of nature. An essential part of this is examining the structure and interactions of matter.

An official website of the United States government

Here’s how you know

Official websites use .gov A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS A lock ( Lock A locked padlock ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

https://www.nist.gov/cybersecurity

Cybersecurity

NIST develops cybersecurity standards, guidelines, best practices, and other resources to meet the needs of U.S. industry, federal agencies and the broader public. Our activities range from producing specific information that organizations can put into practice immediately to longer-term research that anticipates advances in technologies and future challenges.

Some NIST cybersecurity assignments are defined by federal statutes, executive orders and policies. For example, the Office of Management and Budget (OMB) mandates that all federal agencies implement NIST’s cybersecurity standards and guidance for non-national security systems. Our cybersecurity activities also are driven by the needs of U.S. industry and the broader public. We engage vigorously with stakeholders to set priorities and ensure that our resources address the key issues that they face. 

NIST also advances understanding and improves the management of privacy risks, some of which relate directly to cybersecurity.

Priority areas to which NIST contributes – and plans to focus more on – include cryptography, education and workforce, emerging technologies, risk management , identity and access management, measurements, privacy, trustworthy networks and trustworthy platforms.

Additional details can be found in these brief and more detailed fact sheets.

Featured Content

Cybersecurity topics.

• Cryptography
• Cybersecurity education and workforce development
• Cybersecurity measurement
• Identity & access management
• Privacy engineering
• Risk Management
• Securing emerging technologies
• Trustworthy networks
• Trustworthy platforms

The Research

Projects & programs.

Exposure Notification – protecting workplaces and vulnerable communities during a pandemic

Trustworthy Networks of Things

Cryptographic module validation program (cmvp).

Cyber-Physical Systems/Internet of Things for Smart Cities

Additional resources links.

NIST Drafts Major Update to Its Widely Used Cybersecurity Framework

NIST hosts meeting of O-RAN Alliance security experts

NIST Awarded Cyber Policy Award for CSF 2.0 Efforts

NIST Awards $3.6 Million for Community-Based Cybersecurity Workforce Development

Cybersecurity Insights Blog

Protecting model updates in privacy-preserving federated learning: part two, take a tour nist cybersecurity framework 2.0: small business quick start guide, giving nist digital identity guidelines a boost: supplement for incorporating syncable authenticators, protecting model updates in privacy-preserving federated learning, nice webinar: equity strategies in youth apprenticeship programs and partnerships, nice webinar: empowering refugee communities in cybersecurity roles, 2024 iris experts group (ieg) meeting, nist workshop on the requirements for an accordion cipher mode 2024, stay in touch.

Sign up for our newsletter to stay up to date with the latest research, trends, and news for Cybersecurity.

• How It Works
• PhD thesis writing
• Master thesis writing
• Bachelor thesis writing
• Dissertation writing service
• Dissertation abstract writing
• Thesis proposal writing
• Thesis editing service
• Thesis proofreading service
• Thesis formatting service
• Coursework writing service
• Research paper writing service
• Architecture thesis writing
• Computer science thesis writing
• Engineering thesis writing
• History thesis writing
• MBA thesis writing
• Nursing dissertation writing
• Psychology dissertation writing
• Sociology thesis writing
• Statistics dissertation writing
• Buy dissertation online
• Write my dissertation
• Cheap thesis
• Cheap dissertation
• Custom dissertation
• Dissertation help
• Pay for thesis
• Pay for dissertation
• Senior thesis
• Write my thesis

128 High Quality Cybersecurity Research Topics Ideas List

The internet is a global village full of different people. Some people have malicious motives. Once they stumble upon your sensitive data, they will use it to harass you. This also occurs in social media accounts. You may post something and then get some bad or hurtful comments.

That’s a form of cyberbullying that is not acceptable. Therefore, you need to be careful when dealing with people on the internet. Also, try to reduce the data that you expose on your different user profiles. A person may even steal your online identity in a blink of an eye.

Case Situations To Write Cybersecurity Research Paper

Thereby cybersecurity comes in with the motive of defending computers, servers, mobiles, electronic systems, networks, and much more from those malicious attacks. You may need to write a cybersecurity research paper for:

Your final paper, project, thesis, or dissertation. When you are proposing a new strategy to use in your company to prevent cyber-attacks. When you want to bring into light some vulnerabilities being ignored. When you want to do more research and get a better understanding of harassment on the internet.

How To Write Cybersecurity Research Paper

This is the procedure you can use when writing a research paper.

Consult your professor – You will first need to get insights from your professor or teacher on the best way to go about it. You can provide a list of topics you may want to write on for his approval. Brainstorm – Discuss with some like-minded people the best cybersecurity topics to try. You need to be careful to ensure that you choose a topic that you can easily do. Research – Once you settle on a good topic, you can start your research on books, scholarly articles, documentaries, and films to get legit information on your cybersecurity research topic. Jot them down as a draft. Start your paper – Once you are settled with the research, you can use your draft to write a viable research paper. Ensure you follow the right procedure. Proofread the work – Once you are satisfied with your work, consider proofreading it before submitting it.

If you don’t feel like writing research paper yourself, you can get cheap dissertation help from our experts.

Cybersecurity Research Topics

When in high school or college, you need to strive to get good grades. You can use any of these cybersecurity research topics for your paper. Just ensure to do enough research on the concepts.

• The significance of a firewall in the protection of the network.
• Discuss the process of authentication.
• The loss and restoration of data.
• The best data encryption algorithms.
• The best methods to protect your network.
• Evaluate digital piracy and security.
• The significance of social engineering.
• The significance of software updates in devices.
• The major causes of cybersecurity.
• The safety of biometrics.
• The worst cases of IoT hacking.

Cybersecurity Research Paper Topics

Cybersecurity is wide and inexhaustible. Each day, cybercrime are occurring, leading to research on better ways to protect ourselves online. You can use any of these topics for your research paper or project.

• The advantages and disadvantages of unified user profiles.
• The relation between bots and cybersecurity.
• The major cybersecurity vulnerabilities.
• Evaluate digital piracy and its effects on creativity.
• How has automotive hacking grown over the years?
• Evaluate ethical hacking.
• Evolution of phishing over time.
• The best antivirus software currently being used.
• The trends in cybersecurity technology.
• How biometrics is helping in cybersecurity?
• The occurrence of cybersecurity in spoofing.

Cybersecurity Research Topics For Research Papers

Are you in the IT profession? Have you done your project yet? Then you can consider using any of these cybersecurity research topics. They are all ideal and based on current matters.

• The rise of identity theft on the internet.
• Why are more people getting into computer forensics?
• The major threats found using digital forensic techniques.
• The best VPNs in the world that will hide your IP on the internet.
• The disadvantages of exposure of your IP address to the public.
• The major A.I. security systems.
• The centralization of data storage.
• How to identify malicious activity on your devices.
• The safety of a network.
• The applications of network segmentation.
• The major challenges in IT risk management.

PhD Research Topics In Cybersecurity

Are you currently doing your Ph.D.? You can use any of these cybersecurity topics for your paper. They are all based on current matters. There are available resources that you can use to get data.

• The best approach for connected autonomous vehicles.
• The best methods for cognitive cybersecurity.
• The most innovative methods being used to determine the viability of deep learning based on the cybersecurity log analytics system.
• The significance of not sharing sensitive data on social media networks.
• Evaluate cookies on privacy.
• The different types of hackers.
• The disadvantages of Wi-Fi hacking apps on mobile phones.
• The major cyber-attack concepts.
• The best way to develop credible internet security software.
• How to scan malware on your pc.
• Evaluate twitter’s access control policy.

Research Topics In Cybersecurity

You can use any of these research topics in cybersecurity for your papers. You can derive data from some other scholarly articles, documentaries, films, and books. Information about cybersecurity gets updated daily.

• The attack of ransomware.
• The effects of RSA on any network’s security.
• The significance of cloud security.
• How do data leaks occur on mobile apps?
• The effects of a black hole on a network system.
• The significance of applications logging.
• How to detect malicious activities on Google Play apps.
• The best way to check security protocols.
• How does network security deal with cybercrime?
• The network security monitoring process.
• The dangers and flaws of the internet.

Best Research Topics In Cybersecurity

How confident are you about your knowledge of cybersecurity? Then you can consider using any of these topics to test your knowledge capacity. Give it your best to get top grades.

• Initiatives that can be taken to check the growth of cyber hackers.
• The difference between white and black hat hackers.
• How does network intrusion occur and its prevention?
• The authentication processes.
• The most common vulnerabilities.
• The different types of cybercrime.
• The major pandemics caused by cyber viruses.
• The significance of software updates and patches.
• The common laws against cybercrime in the world.
• The best way to suppress the ransomware attack rate.
• The significance of a keylogger.

Hot Topics Cybersecurity Research

These are some of the hottest topics in cybersecurity. You just need to find an ideal topic, do research, jot down the points, and start your research paper.

• The best way to ensure you are safe when downloading files on the internet.
• The best device synchronization and protection methods.
• How can you detect bots on the internet?
• The relation between internet cookies with cybersecurity.
• How are IOS-based apps less prone to ransomware attacks?
• Is it possible for computer hardware to face a cyber-attack?
• The algorithms of data encryption.
• The significance of investing in a strong anti-malware.
• How do encrypting viruses work?
• How do the reverse engineering and vulnerabilities analysis work?

Great Topics For Cybersecurity Research Papers

There are a lot of vulnerabilities on the internet. These great topics for cybersecurity can make you more knowledgeable about the current trends.

• Risk management in computing.
• The most common causes of a data breach in the 21 st
• The best way to protect your device and synchronize the data.
• The significance of computer forensics in the current digital era.
• The major implications of ethical hacking.
• The motivations behind cybercrimes like identity theft.
• The major components of IT and data governance.
• The most secure user authentication methods.
• The threats of digital piracy.
• The significance of device synchronization.

Cybersecurity And Law Research Topics

Did you know that certain laws govern cybersecurity? Then you can use these cybersecurity and law research topics to get a deeper understanding.

• Data and cybersecurity in IoT.
• The correlation between big data analysis with IoT.
• Evaluate Software Defined Network.
• The best tools for excellent email security.
• How to prevent cybercrimes.
• How do phishing scams occur?
• The significance of using strong passwords.
• The worst data breaches of all time.
• How do malicious people use other people’s identities to their benefit?
• How to remove malware from a computer.

Research Topics On Cybersecurity

There are different internet vulnerabilities in the world. Thereby, you can use these research topics on cybersecurity to understand how your security can be compromised on the internet.

• Evaluate botnets in the current world.
• Evaluate a brute force attack.
• The risks of connecting your device to a public wireless network.
• How to secure removable media.
• The occurrence of credit card fraud.
• The most recent cloud security threats.
• The significance of implementing multifactor authentication.
• How is online slandering a cybercrime?
• Email sender spoofing process.
• Stress is caused by periodic cyberbullying.

Cybersecurity Research Topic

Have you ever faced any cyber-attack? How was the experience? These are great topics that can help you become more knowledgeable.

• How to protect yourself from cyberbullying.
• The best security measures to input on Windows, macOS, and Linux.
• How dangerous is cyberstalking?
• Can cyber harassment be termed a crime?
• The major dangers of public Wi-Fi networks.
• Is it possible to identify a phishing attack?
• The best mobile protection methods on your smartphone.
• Malware and how it occurs.
• The best practices to secure your Home Wi-Fi.
• The advantages and disadvantages of antivirus software.

Topic On Cybersecurity

As a student, you need to up your game, to ensure you provide custom work that your teacher or professor will be happy about. Just try any of these topics on cybersecurity.

• The endpoint attacks on devices.
• The dangers posed by tracking cookies.
• The role of backups on your device’s data.
• Evaluate security patches.
• Is it important to read the software terms and conditions?
• Are there any malicious apps on the Google Play Store and Apple Store?
• Evaluate SQL injection attacks.
• The best way to keep your personal information safe.
• The vulnerabilities found in multifactor authentication.
• How to protect your computer.
• How to authenticate on your devices.

Paper Writing Assistance In Cybersecurity Research Paper

Are you busy and wondering how you will do your research paper, project, or thesis? Look no further, you can pay for dissertation and be sure to get perfect result. You just need to order by choosing a topic of your preference and buy it at a cheap price.

You don’t have to worry about not meeting the deadline. With us, you will be sorted. All the best in your research paper.

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Comment * Error message

Name * Error message

Email * Error message

Save my name, email, and website in this browser for the next time I comment.

As Putin continues killing civilians, bombing kindergartens, and threatening WWIII, Ukraine fights for the world's peaceful future.

Ukraine Live Updates

Custom Essay, Term Paper & Research paper writing services

• testimonials

Toll Free: +1 (888) 354-4744

Email: [email protected]

Writing custom essays & research papers since 2008

154 exceptional cybersecurity research topics for you.

If you are studying computer science or IT-related course, you will encounter such a task. It is one of the most technical assignments, primarily in the era of advanced digital technologies. Students may not have the muscles to complete such papers on their own. That is why we provide expert help and ideas to make the process easier.

Do you want to excel in your cybersecurity paper? Here is your number one arsenal!

What You Need To Know About Cyber Security Research Topics

A cybersecurity paper deals with the practices of protecting servers, electronic systems, computers, and networks from malicious attacks. Although most students think this only applies to computers, it also applies to mobile computing and other business models.

There are various categories in cybersecurity, including:

Network security Application security Information security Operational security Disaster recovery and business continuity

Therefore, your cybersecurity topics for research should:

Examine the common security breaches in systems and networks Offer practical ways of protecting computers from such attacks Highlight the legal and ethical implications of hacking and other related practices Point out the challenges encountered in combating cybercrime

Since this is a technical paper, you should endeavor to do your research extensively to prevent rumors and unverified facts. The topics should also inform and educate people who are not conversant with cybersecurity in simple terms. Avoid using jargon at all costs, as this will make the paper difficult to read and understand.

Are you worried about where you can get professional cybersecurity topics and ideas? Well, here are a few of the most reliable sources that can furnish you with top-rated issues.

• Government legislation on cybersecurity (Acts of Parliament)
• The UN Office of Counter-Terrorism (Cybersecurity initiatives)
• The CISCO magazine
• Forbes also has excellent coverage on cybersecurity

You can find impressive topic ideas from these sources and more. Furthermore, news headlines and stories on cybersecurity can also help you gather many writing ideas. If all these prove futile, use our tip-top writing prompts below:

Quality Cyber Security Thesis Topics

• Impacts of coronavirus lockdowns on cybersecurity threats in the US
• Why ethical hacking is contributing to more harm than good
• The role of computer specialists in combating cyber threats before they occur
• Technological trends that are making it difficult to manage systems
• Are passwords reliable when protecting computer systems?
• Effects of having more than one systems administrator in a company
• Can the government shut down the dark web once and for all?
• Why should you bother about the security of your mobile device?
• Evaluate reasons why using public WIFI can be harmful to your security
• The role of cybersecurity seminars and conferences
• How universities can produce ethical computer hackers who can help the society
• How to counter-terrorism with advanced cybersecurity measures
• Impacts of teaching children how to use computers at a tender age
• Latest innovations that are a threat to cybersecurity
• The role of monitoring in combating frequent cyber attacks
• How social media is contributing to cyber attacks
• Discuss the relationship between cyberbullying and cybersecurity
• Why fingerprints may be the best method of protecting devices
• The role of YouTube in contributing to the rising number of hackers

Top Research Topics For Cyber Security For Master Thesis

• Impact of cyber threats on attaining the sustainable development goals
• Why websites are becoming easy to hack in the 21 st century
• Effects of not having an SSL certificate for a website
• Discuss the security threats associated with WordPress websites
• Impacts of frequent maintenance while the website is still running
• How computer colleges can contribute to a safe cyberspace
• Latest cyber threats to business and financial websites
• Discuss the implications of cyber threats on privacy
• The role of Facebook in advancing cyberbullying and hacking
• Is hacking becoming a global epidemic in the digital world?
• Why using Cyber Cafes may be detrimental to your digital security
• The role of systems analysts in responding to data breaches
• How cybersecurity movies are contributing to cyber threats
• Should hackers face lifetime jail imprisonment when found guilty?
• Loopholes in cyber laws that make the practice challenging to curtail

Good Thesis Topics For Cyber Security

• The relationship between privacy and data security in computing
• Why cloud computing offers a haven for computer hackers
• The role of character and human-based behavior in cybersecurity
• How to determine safe organizational security management and policy
• How the Internet of Things is promoting cyber attacks
• Effects of using cracked computer software
• Are biometrics in cybersecurity able to put off hackers?
• The role of studying mobile platform security
• Why companies should frequently monitor their firewalls
• The role of antimalware in curbing cyber attacks
• Why is Ransomware a headache to most companies handling big data?
• How does antivirus software improve the security of your computer?
• Compare and contrast between the security of UNIX and Ubuntu
• The role of data encryption technologies in ensuring system security
• Is the process of encrypting viruses safe?

Top-Grade Thesis Topics For Cyber Security

• Describe the effectiveness of cybersecurity audits on company systems
• Is it proper to conduct device synchronization?
• Why is it difficult to manage the security of an intranet?
• Discuss the effects of logging in to many devices at the same time
• Evaluate the significance of computer forensics
• How are hackers inventing new ways of breaching the systems of companies?
• Why it is necessary to review the data protection laws
• Practices that increase the vulnerability of a system to cyber attacks
• Can organizations implement impenetrable network systems?
• Why administrators should check the background of users before giving them rights and privileges
• The role of risk management cybersecurity
• Discuss the impact of reverse engineering on computing systems
• Effects of a cyber-attack on a company’s economic performance
• What legal frameworks work best for a computer company?
• The role of social engineering in cybersecurity

Information Security Research Topics

• The implication of the proliferation of the internet globally
• Innovative technologies used in keeping off hackers
• The role of information communication technologies in maintaining the security
• Are online courses on informative security practical?
• Why should people avoid sharing their details on Facebook?
• Effects of using your image on social media
• The role of pseudo names and nicknames on social media
• Discuss the implications of Wi-Fi hacking apps on mobile phones
• How to detect malicious activity on a system
• Evaluate the potential threats of conduct self-hacking on a system
• The impact of sharing personal details with hiring agencies
• How con artists lure unsuspecting applicants into giving out their details
• Effects of frequent maintenance on systems
• How to strengthen the firewall of an information system
• The role of the media in propagating security breaches to information systems

Latest Computer Security Research Topics

• Tricks that black hat hackers use to infiltrate company systems
• How children learn about cybersecurity from their parents
• The impact of watching hacking movies and TV series
• How various companies are protecting themselves from cyber attacks
• Why every company should have a systems security consultant
• Discuss the implication of digital piracy
• Threats that biometrics are bringing to digital systems
• How to block a network intrusion before it causes any effect
• Why MacOS is challenging to infiltrate, unlike Windows
• Results of two-step authentication security measures for login systems
• The role of updating computer systems during working days
• Evaluate times of the year when hackers infiltrate systems the most
• Why it isn’t easy to manage big data on the cloud
• What happens during a system breakdown and maintenance?
• Discuss the role of data synchronization in creating a backup

Network Security Research Paper Topics

• The impact of having self-configuring and decentralized network systems
• Effects of ad-hoc networks for large companies
• Discuss the role of wireless sensor networks in contributing to security breaches
• How malicious nodes join a network
• Why it is difficult to detect a passive network attack
• How active network attacks reduce a network’s performance
• Evaluate the various parameters used in network security
• Analyze how a black hole affects a network system
• Describe techniques used in detecting malicious nodes on networks
• How to improve the safety of a company network
• The role of data encryption in maintaining the security of a network
• Describe the various channels of establishing secure algorithms in a network
• How does RSA increase the safety of a particular network?
• Effective policies and procedures for maintaining network security
• The role of a unique ID and Password in securing a website

Computer Security Research Topics

• Why it is challenging to maintain endpoint security
• The role of a critical infrastructure cybersecurity
• How to create secure passwords for your computer network
• The part of scanning for malware often on your PC
• How to detect apps that invade your privacy unknowingly
• Why ordering software from the black market is a threat to security
• Safe computing techniques for first-time computer users
• The role of digital literacy in preventing hacking
• Why most online users fall to online scams
• The role of smartphones in enhancing cybersecurity threats
• Evaluate the mobile landscape concerning data security
• The implication of private email accounts in data breaches
• Sites that contain a barrel of internet criminals
• How to develop comprehensive internet security software
• How children can navigate the internet safely

Impressive Cyber Crime Research Topics

• Why cyber currencies are a threat to online security
• Why cyberbullying is rampant in the 21 st century unlike in any other time
• The impact of online persuasion campaigns on cybersecurity
• Why teenagers are victims of cyberbullying than adults
• Discuss the effects of technology evolution on cybercrime
• How online hackers collect information without the knowledge of the victim
• Traits of a robust cybersecurity system
• Practices that can help reduce cybercrime in institutions of higher learning.
• Effects of global coordinated cyber attacks
• The penalties of cyber-attack in the First Amendment
• Why the world is experiencing increased cyber attacks
• Critical concepts of cyber attacks
• Cybercriminals and enterprises
• Role of NGOs in combating cyber terrorism
• Cyberbullying in campus

World-Class Cyber Security Thesis Ideas

• Effects of the cyber-attack on Sony in 2014
• The role of globalization in enhancing cybersecurity
• How to prevent automotive software from malicious cyber attacks
• The role of cyber technology in changing the world since the 1990s
• How the private sector is essential in combating cyber threats
• Computer infrastructure protection against cyber attacks
• Impact of social networking sites on cybersecurity
• Threats that cyber-attacks pose the national security of a country
• How cyber monitoring affects ethical and legal considerations
• Factors leading to the global nature of cyber attacks
• Analyze law enforcement agencies that deal with cyber attacks
• Evaluate cyber-crime court cases
• Evolution of the cybersecurity industry
• Cyber terrorism in the US
• Implementing adequate data protection strategies

We offer paper writing help on any cybersecurity topic. Try us now!

This is a potential security issue, you are being redirected to https://csrc.nist.gov .

You have JavaScript disabled. This site requires JavaScript to be enabled for complete site functionality.

An official website of the United States government

Here’s how you know

Official websites use .gov A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS A lock ( Lock Locked padlock icon ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

• Drafts for Public Comment
• All Public Drafts
• NIST Special Publications (SPs)
• NIST interagency/internal reports (NISTIRs)
• ITL Bulletins
• White Papers
• Journal Articles
• Conference Papers
• Security & Privacy

Applications

Technologies.

• Laws & Regulations
• Activities & Products
• News & Updates
• Cryptographic Technology
• Secure Systems and Applications
• Security Components and Mechanisms
• Security Engineering and Risk Management
• Security Testing, Validation, and Measurement
• Cybersecurity and Privacy Applications
• National Cybersecurity Center of Excellence (NCCoE)
• National Initiative for Cybersecurity Education (NICE)

Security and Privacy

• digital signatures
• key management
• lightweight cryptography
• message authentication
• post-quantum cryptography
• random number generation
• secure hashing
• cybersecurity supply chain risk management
• general security & privacy
• access authorization
• access control
• Personal Identity Verification
• public key infrastructure
• personally identifiable information
• privacy engineering
• categorization
• continuous monitoring
• controls assessment
• privacy controls
• security controls
• risk assessment
• roots of trust
• system authorization
• advanced persistent threats
• information sharing
• intrusion detection & prevention
• vulnerability management
• accessibility
• testing & validation
• acquisition
• asset management
• audit & accountability
• awareness training & education
• configuration management
• contingency planning
• incident response
• maintenance
• media protection
• patch management
• personnel security
• physical & environmental protection
• program management
• security automation
• reliability
• artificial intelligence
• cloud & virtualization
• combinatorial testing
• personal computers
• quantum information science
• smart cards
• operating systems
• communications & wireless
• cyber-physical systems
• cybersecurity education
• cybersecurity framework
• cybersecurity workforce
• industrial control systems
• Internet of Things
• mathematics
• positioning navigation & timing
• small & medium business

Laws and Regulations

• Comprehensive National Cybersecurity Initiative
• Cybersecurity Strategy and Implementation Plan
• Cyberspace Policy Review
• Executive Order 13636
• Executive Order 13702
• Executive Order 13718
• Executive Order 13800
• Executive Order 13905
• Executive Order 14028
• Executive Order 14110
• Federal Cybersecurity Research and Development Strategic Plan
• Homeland Security Presidential Directive 7
• Homeland Security Presidential Directive 12
• OMB Circular A-11
• OMB Circular A-130
• Cyber Security R&D Act
• Cybersecurity Enhancement Act
• E-Government Act
• Energy Independence and Security Act
• Federal Information Security Modernization Act
• First Responder Network Authority
• Health Insurance Portability and Accountability Act
• Help America Vote Act
• Internet of Things Cybersecurity Improvement Act
• Federal Acquisition Regulation

Activities and Products

• annual reports
• conferences & workshops
• quick start guides
• reference materials
• standards development
• financial services
• hospitality
• manufacturing
• public safety
• telecommunications
• transportation

• About Campus Insider

• Search Search

5 Research Topics in Cybersecurity

In 2022, market and consumer data firm Statista reported that cyberattacks would cost individuals and companies $8.4 trillion globally that year. By 2027, it projected, the cost would rise to $23.8 trillion. Cyberattacks occur when individuals gain unauthorized access to digital systems and information for malicious purposes. Their enormous cost to people and organizations makes it critical to protect systems, software and data against those attacks.

The term “cybersecurity” refers to efforts to protect corporate or personal electronic equipment against these costly attacks. Understanding the vulnerabilities that can allow unauthorized and damaging access to digital systems is a key component in cybersecurity research. An advanced degree in information security management can help professionals learn how cybersecurity risks are evolving, what cybersecurity risks to look for in their own organizations and how to address them.

What Is Cybersecurity Research?

Cybersecurity research focuses on reviewing digital tools and processes to reveal potential vulnerabilities. Research on cybersecurity topics ranging from the Internet of Things (IoT) to work-from-home (WFH) information security can help people and companies stave off data breaches in those key areas.

Cybersecurity professionals can rely on computer science research tactics such as testing web browsers and online applications to uncover areas that a hacker could exploit to gain unauthorized data access. They can also turn to empirical research that examines issues related to cybersecurity from various angles, from criminal science to international relations, and that offers approaches to address those concerns.

In fact, conducting research about potential security threats and information technology (IT) trends is a key responsibility of cybersecurity professionals, such as information security analysts.

Why Is Cybersecurity Research Important?

The value of cybersecurity research is growing due to the proliferation of connected devices that allow cybercriminals to access digital information — and as the costs associated with successful cyberattacks increase.

The origin of cyberattacks can be computers and the systems that run them, but it can also be any of hundreds of everyday devices that use technology to collect and share data. From smartphones to medical equipment, the tools that cyberattackers can compromise generate or store a staggering amount of data.

Statista reports that the amount of data created, copied, downloaded and read globally in 2010 was 2 zettabytes. By 2025, Statista predicts, the capacity of the data in use around the world will reach 181 zettabytes.

The growth in the use of data is occurring alongside a host of issues, from COVID-19-related disruptions to geopolitical events, that can make the technology that shares and stores it more vulnerable to attack. Conducting research on cybersecurity topics can assist IT professionals in protecting these large amounts of data during challenging times by helping them:

• Understand the vulnerabilities of digital tools and processes
• Determine the significance of data breach impacts
• Prioritize their efforts to ensure protection of critical information

5 Current Research Topics in Cybersecurity?

Today’s most pressing research topics in cybersecurity go beyond password protection and firewalls. A global pandemic, geopolitical events and technological advances are also behind some key topics that are now driving cybersecurity research. Below are five of those top cybersecurity research topics.

1. Artificial Intelligence

Artificial intelligence (AI), in which machines complete tasks that traditionally had required humans to perform, today is helping computing professionals observe and analyze activity related to large amounts of digital data. The efficiency of using AI for cybersecurity can lead to significant savings as organizations respond to data compromises. The shortened response time led companies to an average of $3 million in savings in those situations, according to a 2022 report from IBM.

One key research topic for cybersecurity professionals is how best to use AI to find potential vulnerabilities and remove them — before cyberattackers use that same technology to find those security risks and exploit them.

However, AI in the wrong hands can also present a cybersecurity risk. AI can also be a tool for misusing data, with cybercriminals relying on this technology to create inauthentic emails and phone messages to trick users into providing personal data. The increasing reliance on AI makes this issue even more important for cybersecurity researchers, with Statista projecting in 2022 that the AI software market would reach $126 billion around the world by 2025.

2. Digital Supply Chains

Digital supply chain systems monitor and evaluate the functions of each party in the chain, to help them produce and distribute products more efficiently. Hackers can exploit the technology used in this process, making cyberattacks an additional threat to supply chains already experiencing disruptions related to the pandemic.

For example, technology research firm Gartner, predicted in 2022 that by 2025, a total of 45 percent of companies would suffer digital attacks on their supply chains. This percentage is three times higher than the percentage from 2021. A 2022 report from cybersecurity company Venafi found that 82 percent of chief information officers feared that their organizations’ supply chains were vulnerable to this type of attack.

Cybersecurity professionals today are investigating potential digital security risks in supply chains, while corporate leaders are seeking out suppliers that focus on researching — and correcting — these vulnerabilities.

3. Internet of Things

The IoT refers to the ability to connect almost any device with the internet and with other connected tools. From kitchen appliances to wearable fitness gadgets, numerous products and tools are part of the IoT. Statista reported in 2022 that more than 11 million devices were digitally connected in 2021. The firm also projected that more than 29 billion devices would be IoT connected by 2030.

The many devices that rely on the IoT measure and process vast amounts of data, and the networks and cloud systems that hold and share that data present a host of security risks. A key area of cybersecurity research has been tracking these vulnerabilities. Manufacturers, consumers and governments have begun using the knowledge gathered by cybersecurity researchers to establish practices and policies that safeguard against the risks these researchers are finding.

4. State-Sponsored Attacks

Cyberattacks from government actors seeking state secrets are nothing new, but a growing trend is for hackers seeking this unauthorized access to target organizations and individuals with no government affiliation. The ultimate goal can be intelligence, technology theft, supply chain disruption or even influencing internal politics through disinformation.

A 2022 Forbes article noted that in 2023, more than 70 nations were set to conduct elections, and the digital activities related to these events, including reports about them, are a frequent target of hostile government actors. Additionally, countries involved in armed conflicts increasingly rely on cyberattacks to gain advantage over enemy governments, even when it involves interfering with the work of private companies and citizens.

These trends have made it critical for cybersecurity researchers to learn more about potential vulnerabilities in government networks, attacks on private companies that can impact critical infrastructure, and the security of elections.

5. Working From Home

Fueled by pandemic restrictions, the number of WFH employees exploded in recent years. The number of remote workers will reach more than 36 million in the U.S. by 2025, according to 2020 projections from freelancing platform Upwork.

The many employees based at off-site locations have made managing data security difficult for companies, whose workers may use unprotected devices to access and transmit business information. That leaves the employees vulnerable to attacks that target sensitive data or threaten malicious activity unless the company meets the hackers’ demands.

Adding to the security risk is the proliferation of work and other activity that requires the use of the internet and internet-based tools like videoconferencing. A 2021 Pew Research Center survey showed that 40 percent of Americans had relied on these types of tools and processes in new ways since the pandemic began in early 2020. Cybersecurity professionals are studying how best to protect employees — and the corporate data they use in their work — from cyberattackers.

Take a Leadership Role in Cybersecurity

Cybersecurity research can shed light on issues with data protection — and the tools and processes that provide it. If you’re ready to help guide your organization’s response to cybersecurity issues, explore Augusta University Online’s Master of Science (MS) in Information Security Management program.

Through online courses focused on Certified Information Systems Security Professional (CISSP) certification elements, students can gain the knowledge to help their employers navigate today’s cybersecurity challenges. Explore how AU Online’s MS in Information Security Management can help you reach your career goals.

Built In, “What Is Artificial Intelligence?” Cybersecurity and Infrastructure Security Agency, Cyber Threats and Advisories Forbes, “The Top Five Cybersecurity Trends in 2023” Gartner, “7 Top Trends in Cybersecurity for 2022” IBM, “Cost of Data Breach 2022: A Million Dollar Race to Detect and Respond” IBM, What Is Cybersecurity? Journal of Cybersecurity, About the Journal Microsoft, What Is a Cyberattack? Network World, “What Is IoT? The Internet of Things Explained” Oracle, “Digital Supply Chain Explained” Pew Research Center, “The Internet and the Pandemic” Statista, Estimated Cost of Cybercrime Worldwide From 2016 to 2027 Statista, Number of Internet of Things (IoT)-Connected Devices Worldwide From 2019 to 2021, With Forecasts From 2022 to 2030 Statista, Revenues From the Artificial Intelligence (AI) Software Market Worldwide From 2018 to 2025 Statista, Volume of Data/Information Created, Captured, Copied, and Consumed Worldwide From 2010 to 2020, With Forecasts From 2021 to 2025 TechRadar Pro, “Why Cybersecurity Research Is Now More Important Than Ever” The Conversation, “5 Ways the COVID-19 Pandemic Has Forever Changed Cybersecurity” Upwork, Upwork Study Finds 22% of American Workforce Will Be Remote by 2025 U.S. Bureau of Labor Statistics, Information Security Analysts Venafi, “Study: 82% of CIOs Say Their Software Supply Chains Are Vulnerable” Vivaldi, “An Insight Into Security Research and Ethical Hacking”

Augusta University Online

Related articles.

Health Information Management vs. Health Informatics

Addressing Health Disparities in Public Health

Public Health Educator: Salary and Job Description

Remote Learning Resources for Students and Teachers

Top 111+ Stunning Cybersecurity Research Topics For 2023

Are you confused about cybersecurity and its research topics? So here, in this blog, we will discuss cybersecurity research topics. This article is important If you are studying computer science or a cybersecurity course.

If you want good grades in cybersecurity research topics, you should pick the latest cybersecurity research topics for your academic exam or test. Here, you can choose the good and latest cybersecurity research topics.

You know that cybercrime is increasing day by day because millions of people use the internet. Several applications deal with the internet, and people normally use the internet for bank transactions, food delivery, online shopping, social media, gaming, etc. Attackers can steal your information, data, and money with the help of malicious software, So we need cybersecurity services.

What is Cybersecurity?

Table of Contents

Cybersecurity is a process of preventing unauthorized access or protecting networks, devices, and data from digital attacks. Cybersecurity is also known as IT(Information Technology)Security which is designed to prevent threats against network systems, applications, and other platforms. In simple words, It prevents or protects any information, data, and others.

Here Are Some of the Best Writing Tips From Statanalytica’s Expert

As you might already know that a well-planned action and a set of useful tools will also help you write a high-quality research paper. On the other hand, remaining motivated throughout the process.

• By choosing an interesting topic for your research paper.
• Conduct some research to find reputable sources.
• Clearly state your cybersecurity thesis.
• A rough plan should be created.
• Finish your paper by drafting it.
• Make sure your content is properly formatted.
• Make sure you understand the assignment before you begin writing your research paper.

Let’s Discuss the 111+ Stunning Cybersecurity Research Topics

Below we listed 111+ cybersecurity research topics that can be used in 2023:

Top 10 Cyber Security Topics of 2023

Here are the top 10 cyber security topics of 2023:

• Can strong passwords protect information?
• Is security in critical infrastructure important?
• The importance of end-user education
• Cloud security posture management
• How does malware work?
• The principle of zero trust access
• 3 phases of application security
• Should removable media be encrypted?
• The importance of network security
• Do biometrics ensure the security of iPhones?

Latest Cybersecurity Research Topics of 2023

• Is removable media a threat?
• Cybersecurity standards for automotive
• How to prevent social engineering attacks
• Security breaches of remote working
• How to prevent phishing attacks
• Physical security measures in banks
• Privacy settings of social media accounts
• Blockchain security vulnerabilities
• Why should you avoid public Wi-Fi?
• How does two-factor authentication work?
• Cryptography
• Discuss the importance of intranet security
• Rise of Automotive Hacking
• What is ethical hacking? 
• The evolution of phishing and how it is becoming more sophisticated
• Which antivirus software is the best in the world?
• The most up-to-date and trending cybersecurity technology
• How can organizations prevent network attacks?
• What is Digital Piracy?
•  Application of biometrics in cyber security?
• Identity theft on the Internet
• Risk management in computing
•  Rise of computer forensics
• Threats are analyzed using digital forensic techniques
• What is a Remote Access VPN?
•  Digital security and Social Networks
• The risks of using public Wi-Fi networks
• Popular online scams in 2022
• Artificial intelligence security systems

Network Security Research Topics 

• Data storage centralization
• Identify Malicious activity on a computer system.
• Importance of keeping updated Software 
• wireless sensor network
• What are the effects of ad-hoc networks 
• How can a company network be safe?
• What are Network segmentation and its applications?
• Discuss Data Loss Prevention systems 
• Discuss various methods for establishing secure algorithms in a network.
• Talk about two-factor authentication

Topics for Application Security Research

• Discuss SQL injection attacks.
• Inadequately configured security protocols.
• Talk about data leaks in mobile apps.
• Backend access control is critical.
• Logging has many advantages for applications.
• Malicious apps are available on Google Play.
• AI applications: ethical constraints and opportunities.
• What is the effect of insecure deserialization?
• The most effective application security testing practices.
• Apps are vulnerable to XSS attacks.

 Information Technology Security Research Topics

• Why should people avoid sharing their details on Facebook?
• What is the importance of unified user profiles?
•  Discuss Cookies and Privacy 
• White hat and black hat hackers
• What are the most secure methods for ensuring data integrity?
• Talk about the implications of Wi-Fi hacking apps on mobile phones
• Analyze the data breaches in 2022
• Discuss digital piracy in 2022
• critical cyber-attack concepts
• Social engineering and its importance

Operational Security Research Topics In 2023

• Securing containerized applications in cloud environments.
• Implementing secure remote access policies for remote workers.
• Evaluating the effectiveness of endpoint protection solutions.
• Protecting against DNS tunneling attacks.
• Securing cloud-based storage solutions.
• Developing secure mobile device management policies.
• Analyzing the effectiveness of honeypots in detecting attacks.
• Securing software supply chains against attacks.
• Investigating the effectiveness of deception technologies in cybersecurity.
• Developing secure network segmentation strategies.
• Evaluating the effectiveness of network traffic analysis solutions.
• Analyzing the effectiveness of two-factor authentication in securing systems.
• Securing critical infrastructure against cyber threats.
• Developing secure email policies to prevent phishing attacks.
• Investigating the use of artificial intelligence in cybersecurity.
• Developing secure DevOps practices.
• Analyzing the effectiveness of security information and event management (SIEM) solutions.
• Securing the Internet of Things (IoT) devices.
• Evaluating the effectiveness of password management solutions.
• Developing secure incident response strategies.

Topics for a Research Paper on CyberCrime Prevention

• Criminal Specialization. 
• Drug Courts. 
• Capital Punishment. 
• Criminal Courts. 
• Crime Prevention. 
• Community Corrections. 
• Criminal Law. 
• Criminal Justice Ethics. 

Computer and Software Security Research Topics

• Learn algorithms for data encryption.
• Concept of risk management security.
• How to develop the best internet security software.
•  What are Encrypting viruses- How does it work?
• How does a Ransomware attack work?
• Scanning of malware on your PC.
• Infiltrating a Mac OS X operating system.
• What are the effects of RSA on network security?
• How do encrypting viruses work?
• DDoS attacks on IoT devices.

Computer and Software Cyber Security Topics

• The importance of updating computer software.
• How to safeguard your computer against malware and other threats.
• The best security practices for your computer and software.
• The various types of cyber security threats and how to avoid them.
• The significance of cyber security education and awareness.
• The importance of cyber security in protecting critical infrastructure.

Data Security Research Topics

• Importance of backup and recovery.
• Benefits of logging for applications.
• Understand physical data security.
• Importance of Cloud Security.
• In computing, the relationship between privacy and data security.
• Discuss the effects of a black hole on a network system.

Application Security Topics

• Detect Malicious Activity on Google Play Apps.
• Dangers of XSS attacks on apps.
• Insecure Deserialization Effect.
• Check Security protocols.

CyberSecurity Law Research Paper Topics

• Strict cybersecurity laws in China.
• Importance of the Cybersecurity Information Sharing Act.
• USA, UK, and other countries cybersecurity laws.
• Discuss The Pipeline Security Act in the United States.

If you are interested in criminal research topics, then here are the best criminal justice research topics for you.

How to Choose The Best Cybersecurity Research Topics in 2023

There are a few factors to consider when selecting cybersecurity research topics. The first and main thing to consider is to ensure that the topic is current and relevant. Because cyber security is a changing field. As a result, it is very crucial to select a topic that will be relevant for a few months.

On the other hand, the second thing to consider is to select an interesting and engaging topic. Because cyber security can be a dry subject, it is critical to select a topic that will keep readers interested.

Finally, it is very important to select a researchable topic. There are several cybersecurity topics available, but not all of them are simple to research. Choose a topic about which there is a lot of information.

• Determine your target audience
• Define your research objectives
• Choose a topic that your audience will find both interesting and relevant
• Conduct preliminary research to ensure that there is sufficient information available on your chosen topic
• Make sure your topic is focused enough to fit into a single research paper

Research Area in Cyber Security

Cybersecurity is extensive, and constantly evolving field. On the other hand, its research takes place in many areas:

• Quantum & Space 
• Data Privacy 
• Criminology & Law
• AI & IoT Security

Get More Cybersecurity Research Topics

In this blog, we have covered the 111+ best cybersecurity research topics. These cybersecurity topics help in your exam or test. If you have any difficulty with cybersecurity research topics, you can take cybersecurity research paper help or research paper assignment help at a very affordable price.

Here are some of the benefits of taking cybersecurity research topics help from us.

• 24 Hours Availability
• On-time Delivery
• Free Corrections
• Money-Back Guarantee
• Affordable Deals
• Professional Experts

You can contact us any time and impress your teacher by choosing a good cybersecurity research topic.

This is the end of the post, which is about cybersecurity research topics. On the other hand, we mentioned 111+ stunning cybersecurity research topics for 2023 offer an excellent opportunity for researchers to explore and address critical cybersecurity challenges. However, the ever-evolving technological landscape presents new security challenges every day, and it is essential to keep up with the latest trends to stay ahead of cyber threats. 

On the other hand, these research topics provide many areas to explore, from network security, the internet of things, and software security to network security, cryptography, and data security. I hope you like this post.

Q1. What are the types of cyber security threats?

There are several different types of cyber security threats. More popular are Trojan horses, worms, ransomware, and phishing scams. These types of threats can be very dangerous for the cyber system.

Q2. What are the most controversial topics in criminal justice?

1. Prisoners being granted the right to work 2. Carrying a concealed weapon 3. Prison rape and violence 4. Plea agreement/bargain 5. Rehab vs. reform. 6. Is an eyewitness testimony effective? 7. Enforcement and effectiveness of stalking laws. 8. Rape culture and the victim’s rights

Q3. What are the main cyber threats of 2023?

There are multiple cyber security threats, but the main social threats of 2023 are email impersonation and phishing.  On the other hand, email impersonation is a phishing technique in which a fake email address that appears to be legitimate is used. 

Related Posts

Step by Step Guide on The Best Way to Finance Car

The Best Way on How to Get Fund For Business to Grow it Efficiently

• Advanced Persistent Threats (APTs)
• Cyber Attack
• Data Breach
• Insider Threat
• Social Engineering
• Supply Chain Attack
• Vulnerability
• DOWNLOAD REPORTS
• REPORT OPPORTUNITIES
• PUBLISH YOUR OWN REPORT
• UPCOMING WEBINARS
• ON-DEMAND WEBINARS
• Marketing Kit

BlackBasta Ransomware targets Synlab Italia

Dealing with stolen data in ransomware attacks: a comprehensive guide, don’t overlook the cyber risks for operational technology, ai could transform detection and response as legacy mdrs lack.

• Education & Career

Cybersecurity Research Topics for Beginners: Exploring the Fundamentals

In today’s digital landscape, cybersecurity has become a critical concern for individuals and organizations alike. Aspiring cybersecurity researchers often wonder where to start and what areas to explore. This article aims to provide a comprehensive list of cybersecurity research topics suitable for beginners, helping them delve into the fundamentals of this rapidly evolving field. By focusing on these areas, newcomers can gain a solid foundation and understanding of cybersecurity principles and practices.

Password Security: Investigate different password security techniques, such as password hashing algorithms, two-factor authentication (2FA), and biometric authentication. Analyze their effectiveness and explore potential vulnerabilities and countermeasures.

Malware Analysis: Explore malware types, their behavior, and the techniques used for analyzing and detecting them. Investigate malware’s propagation methods, evasion techniques, and methods for identifying and mitigating potential threats.

Network Security: Study network protocols, such as TCP/IP, and analyze common network attacks like DDoS, phishing, and man-in-the-middle attacks. Research network security mechanisms, such as firewalls, intrusion detection systems (IDS), and virtual private networks (VPNs).

Web Application Security: Examine common web vulnerabilities like cross-site scripting (XSS), SQL injection, and cross-site request forgery (CSRF). Learn about secure coding practices, web application firewalls (WAFs), and vulnerability scanning tools.

Cryptography: Dive into the world of cryptography, studying symmetric and asymmetric encryption, digital signatures, and cryptographic algorithms. Explore topics like key management, secure communication protocols, and encryption in different contexts.

Social Engineering: Investigate the human element of cybersecurity by exploring social engineering techniques and tactics used to manipulate individuals. Analyze real-world case studies and research effective prevention and awareness strategies.

Incident Response: Explore the incident response lifecycle, from detection and containment to recovery and lessons learned. Study incident response frameworks, incident handling tools, and best practices for mitigating and managing security incidents.

Mobile Security: Research the unique security challenges posed by mobile devices, including app vulnerabilities, data leakage, and mobile malware. Investigate mobile device management (MDM), secure coding practices for mobile applications, and secure app distribution.

Internet of Things (IoT) Security: Examine the security risks associated with IoT devices, including privacy concerns, data integrity, and device authentication. Explore IoT security architectures, protocols, and solutions for securing interconnected devices.

Ethical Hacking and Penetration Testing: Learn the techniques and methodologies used by ethical hackers to identify vulnerabilities in systems. Study penetration testing frameworks, tools, and methodologies, and understand the importance of responsible disclosure.

Embarking on a journey into cybersecurity research can be both exciting and challenging. By exploring these fundamental topics, beginners can develop a strong understanding of key concepts and acquire the necessary skills to navigate the vast cybersecurity landscape. Remember to stay updated on emerging threats, engage in practical exercises, and foster a continuous learning mindset. With dedication and curiosity, aspiring cybersecurity researchers can contribute to creating a safer digital environment for all.

RELATED ARTICLES MORE FROM AUTHOR

Thinking about a career in software security follow this path, understanding cat culture in cybersecurity: collaboration, awareness, and training, unveiling the true purpose of cyber fraud fusion centers: strengthening digital defense, no posts to display, new reports.

2024 Cloud Security Report [Fortinet]

2024 Application Security Report [Fortinet]

2024 Security Service Edge Report [HPE]

2024 VPN Risk Report [HPE]

Block title.

EDITOR PICKS

The quantum security challenge: data resilience around the unknown, popular posts, list of countries which are most vulnerable to cyber attacks, top 5 cloud security related data breaches, top 5 pci compliance mistakes and how to avoid them, recent posts, knowbe4 to acquire egress email security.

• Terms of Service
• Advertise With Us
• Internships

March 5, 2024

10 Cybersecurity Topics to Cover in 2024

As we navigate through the complex and ever-evolving digital landscape of 2024, the significance of cybersecurity has escalated dramatically. With advancements in technology moving at a breakneck pace, both individuals and organizations are confronted with multifaceted cybersecurity challenges. To navigate these challenges effectively, it is essential to understand and address the key cybersecurity topics of today. This article aims to delve into these topics, emphasizing the critical role of security awareness and proactive measures, alongside the pivotal importance of human risk management in mitigating these threats.

1. Social Engineering

Social engineering remains a significant threat within the cybersecurity domain, cleverly exploiting human psychology rather than relying solely on technical vulnerabilities to gain unauthorized access to systems, data, or personal information. Common tactics include phishing, pretexting, and baiting, with phishing being particularly nefarious due to its role in business email compromise (BEC) schemes. These attacks, often orchestrated by malicious actors, underscore the necessity for heightened awareness and critical scrutiny of unsolicited communications. To bolster protection against social engineering, it is crucial to educate employees on the importance of verifying sources and recognizing common phishing indicators, thereby reducing the attack surface available to attackers. Incorporating security awareness training on these topics can significantly enhance an organization's resilience against these forms of manipulation. 

2. Ransomware

Ransomware continues to be a formidable threat in 2024, with malicious actors locking access to critical data or systems and demanding ransom for their release. This form of attack has seen a diversification in methods, including sophisticated phishing campaigns aimed at facilitating business email compromise. Preventative measures are essential for protection against ransomware threats, emphasizing the importance of regular data backups, timely security updates, and comprehensive phishing awareness programs to educate employees on the risks and mitigation strategies. Security awareness training topics should cover the nuances of ransomware attacks, equipping employees with the knowledge to identify and respond effectively to such threats.

3. Password Management

In the face of advanced cybersecurity threats, robust password management has become a cornerstone of digital protection. The limitations of traditional password strategies have paved the way for the adoption of password managers and the implementation of multi-factor authentication (MFA), enhancing access security. Promoting awareness around the creation and management of strong, unique passwords across different accounts, coupled with regular updates, is crucial for maintaining a secure digital environment. Educating users on the dangers of password reuse and the benefits of using advanced authentication methods can further secure digital identities against unauthorized access.

4. Mobile Security

The increasing reliance on mobile devices has expanded the attack surface for cyber threats, making mobile security a critical area of focus. Common threats include app-based risks, unsecured Wi-Fi connections, and the physical theft of devices. Recommendations for enhancing mobile device protection include the use of VPNs, commitment to regular software updates, and practicing secure app usage, all aimed at safeguarding access to sensitive information. Additionally, enforcing device encryption and secure lock-screen mechanisms can provide an extra layer of security against unauthorized access, especially in case of device loss or theft.

5. Cloud Security

The shift towards cloud services has introduced unique security challenges, particularly concerning data breaches and insecure APIs. Strategies for cloud environment protection emphasize the shared responsibility model, highlighting the importance of access management and the implementation of effective threat detection mechanisms. Regular security assessments and the adoption of robust encryption methods for data at rest and in transit are critical for safeguarding sensitive information stored in the cloud. Ensuring cloud security necessitates a comprehensive focus on protection measures, including regular security assessments and adherence to best practices for securing data access. 

6. Data Privacy

The importance of data privacy has surged in 2024, with new regulations and increased consumer awareness driving the need for enhanced protection measures. Technologies such as encryption play a vital role in securing data, alongside practices like data masking. Implementing strict data handling and retention policies can also contribute to maintaining privacy and complying with regulatory requirements. Maintaining data privacy requires ongoing awareness efforts, regular privacy audits, and updates to privacy policies to ensure robust protection of sensitive information. 

7. Remote Working

The rise of remote working has introduced new cybersecurity vulnerabilities, necessitating a focus on securing home networks and managing the use of personal devices for work purposes. Effective strategies for securing remote work environments include the use of secure connections, adoption of endpoint detection and response (EDR) tools, and the deployment of comprehensive training programs to increase employee awareness and resilience against cyber threats. Human Risk Management plays a crucial role in this context, emphasizing the need for ongoing security awareness training to address the evolving challenges of remote work. As remote work becomes increasingly prevalent, organizations must adapt their cybersecurity measures to protect sensitive data and mitigate the risks associated with remote access.

8. AI and Machine Learning

AI and machine learning have become integral to enhancing cybersecurity defenses, offering advanced capabilities in threat detection and automated security responses. However, these technologies also present potential vulnerabilities that require vigilant monitoring and management to prevent exploitation by malicious actors. The balance between leveraging AI for protection and addressing its inherent risks is crucial for maintaining a strong cybersecurity posture. As AI and machine learning technologies continue to evolve, organizations must remain vigilant in assessing their cybersecurity implications and implementing appropriate safeguards to protect against emerging threats.

9. Internet of Things

The proliferation of IoT devices has significantly increased the attack surface for cyber threats. Securing these devices involves strategies such as network segmentation, regular firmware updates, and strong authentication measures, underscoring the importance of comprehensive awareness and protection efforts to mitigate the risks associated with IoT environments. As IoT adoption continues to grow, organizations must prioritize IoT security measures to prevent unauthorized access and protect sensitive data from exploitation.

10. Human Risk Management

The role of human behavior in cybersecurity cannot be overstated, with strategies for reducing human error encompassing comprehensive security training and awareness programs. Cultivating a security-conscious culture within organizations is essential for enhancing overall protection and mitigating the risks posed by cyber threats. Security awareness training plays a pivotal role in human risk management, providing employees with the knowledge and skills to navigate the complex cybersecurity landscape effectively. Organizations must prioritize security awareness training topics that address human-centric vulnerabilities and promote a culture of cybersecurity awareness.

Step Forward in Cybersecurity with Living Security

In summary, navigating the cybersecurity landscape of 2024 demands a multifaceted approach, combining technological solutions with an emphasis on human risk management to address the myriad of challenges presented. By fostering awareness, implementing robust protection strategies, and focusing on critical areas such as access control, threat detection, and employee education, individuals and organizations can significantly enhance their security posture. Living Security stands ready to lead this journey, offering innovative solutions that seamlessly integrate into comprehensive cybersecurity strategies. Embrace the next step in cybersecurity with Living Security, and strengthen your defenses against the evolving digital threats of today and tomorrow.

The future of cybersecurity

With TikTok in the hands of 170 million Americans, cybersecurity expert Amy Zegart says it’s time to talk about consequences. Foreign access to all that data on so many Americans is a national security threat, she asserts.

For those as concerned as she, Zegart has good news and bad. The government has gotten better at fighting cyberthreats, but artificial intelligence is making things very complicated, very fast. The US needs to adapt quickly to keep pace, Zegart tells host Russ Altman on this episode of Stanford Engineering’s The Future of Everything podcast.

Listen on your favorite podcast platform:

Related : Amy Zegart , senior fellow at The Hoover Institution, Freeman Spogli Institute for International Studies (FSI), and Stanford Institute for Human Centered Artificial Intellligence (HAI)

[00:00:00] Amy Zegart: What we really need to pursue much more seriously is developing independent capacity. Developing the talent, developing the compute that, I know at Stanford's been really pushing this idea of a national AI, research resource. That's fancy talk for compute power so that independent researchers can ask hard questions, uh, and do the kind of analysis that, that needs to be done.

[00:00:27] I think we need to be investing much more in that. Compute is a strategic national asset like oil. And the government should be investing orders of magnitude more and making that available.

[00:00:44] Russ Altman: This is Stanford Engineering's The Future of Everything podcast, and I'm your host, Russ Altman. If you're enjoying the show or if it's helping you in any way, please consider sharing it with friends, family, and colleagues. Personal recommendations are one of the best ways to spread the news about the podcast.

[00:00:59] Today, Amy Zegart from Stanford University will tell us about cybersecurity and AI. How have things changed in the last three or four years since she was last a guest on The Future of Everything? It's the future of cybersecurity. 

[00:01:13] Before we get started, a quick reminder that if you're enjoying this show, please consider sharing it with friends and family. Personal recommendations really do work in growing the podcast audience and improving the podcast.

[00:01:31] Cybersecurity is a huge issue for the United States. Computers are one of the battlefields where the next big conflicts are and will be waged. Specifically, we focus on four countries that are the source of lots of cyber attacks. These include Russia, China, North Korea, and Iran. Intelligence is complicated, and it's gotten more complicated in the last few years with the rise of AI.

[00:01:55] Now, disinformation can be generated and spread more quickly and more realistic looking. Amy Zegart is a senior fellow at the Hoover Institute, the Freeman Spogli Institute for International Affairs, and the Institute for Human Centered AI at Stanford University. She's an expert in cybersecurity. She's written several books and she's an advisor to the nation.

[00:02:17] She's going to tell us that AI has accelerated the work of both the good guys trying to combat cyber warfare and cyber attacks, as well as, unfortunately, the bad guys who are making the attacks. However, things are looking better and there's reason to be optimistic. Amy, you're a return visitor to The Future of Everything.

[00:02:37] It's a great honor for me. You can decide if it's an honor for you or not. Last time we discussed cyber security and you said something very memorable, which is that the cyber security world is moving at light speed and the government is moving at government speed. Now in the interim, since you were last on the show, there's this thing called AI that has just exploded. ChatGPT and many other technologies. Has that changed the situation? Is the government able to respond faster? Are the cyber attacks able to come faster? Both, neither. Where are we these days with respect to the relative strengths of the government and of the cyber attackers? 

[00:03:18] Amy Zegart: Well, Russ, thanks for starting me off with such a softball question. It's really an honor to be back with you too. It's a complicated question. There's good news and bad news. Let me start with the good news. Government has matured. So part of the challenge, as you know, of dealing with cyber is do we have capacity in the government to understand and coordinate and work with the private sector?

[00:03:40] That's gotten a lot better. So we have the creation of the National Cyber Director. That office has matured. There's a state department ambassador at large for cyber. That's a really important component to it. Um, secondly, there are SEC regulations now. 

[00:03:55] Russ Altman: Wow. 

[00:03:55] Amy Zegart: So there's an incentive for corporate boards to pay much more attention to cyber security. And when the incentives are aligned, of course, companies pay more money for cybersecurity, do a lot more investing in cybersecurity. So that, those SEC rules have kicked in. And I think that's important to bear in mind. 

[00:04:12] Russ Altman: Can you, just to take, just to dive down, why would the SEC, why does the SEC even regulate that? I'm a little bit surprised. I think of them as regulating, you know, disclosures about the company and the financials and all that kind of stuff, monopolies, where does cybersecurity come into their kind of purview?

[00:04:28] Amy Zegart: I think there's a sense that it's a question of governance and it's not, the SEC regulations aren't dictating specific cybersecurity actions, but they are incentivizing processes. So corporate directors are held responsible for oversight of cybersecurity. And that's then catalyzed a whole bunch of other things, you know, regular reporting and in private and public companies as well. 

[00:04:53] Russ Altman: And it's not the case that the companies would have been independently motivated not to be attacked, not to have ransomware? I'm just surprised that we needed to tell them this. 

[00:05:02] Amy Zegart: Well, many companies are incentivized. When you think about financial services, for example, they've invested an enormous amount of money in their cyber security, and they know they need to. But many companies think that cyber security is really for the big guys. Cyber security is for the sexy industries. Remember Home Depot? When Home Depot got hacked? 

[00:05:20] Russ Altman: Yes.

[00:05:20] Amy Zegart: Right? Their defense was, we just sell hammers. Why are we a victim of cyber attacks? So, when you think about, 

[00:05:27] Russ Altman: Now the bad guys know about my wheelbarrow. 

[00:05:30] Amy Zegart: Exactly. So when you think about the cyber attack surface, it's everywhere. So you really want to incentivize all companies to spend more money and pay more attention to cybersecurity. I think that's, 

[00:05:41] Russ Altman: Sorry, I interrupted you on that because I was just surprised. Keep going. Yeah. 

[00:05:44] Amy Zegart: So that's the plus side of the ledger. The negative side of the ledger, and you asked about AI, is AI makes everything more complicated and faster. So is AI being used to automate cybersecurity on the defensive side? Yes. Is AI used to automate offensive attacks against cybersecurity defenses? Yes.

[00:06:04] So it sort of washes out. It's good news and bad news on that side. But let me add one other, uh, depressing wrinkle to the story, which is, of course, what are the attackers thinking? What are their capabilities? And what are their intentions? And there, the picture is bad. So I want to read to you the intelligence threat assessment, the annual intelligence threat assessment that was just delivered last month by the Director of National Intelligence to Congress. And this is about China. This is what the intelligence community’s assessment said.

[00:06:38] If Beijing believed that a major conflict with the United States were imminent it would consider aggressive cyber operations against U.S. critical infrastructure, by the way, that means just about everything, and military assets. It goes on to say, designed to induce societal panic.

[00:07:02] What they're saying is, it's not just if a war breaks out, if China believes conflict is imminent, they're already in our systems. And they have an incentive and an interest in attacking. So the bad guys are out there. Just because they haven't attacked us yet, doesn't mean they won't. So when you think about nation states with real cyber capabilities, China, Russia, Iran, North Korea, they're out there and they have not been defeated on the cyber landscape.

[00:07:30] Russ Altman: I'm glad you mentioned our favorite four countries because, uh, because I wanted to ask you, are they, are there, I'm suspecting that their interests are not precisely aligned and that they all have a different kind of, uh, piece of the game in mind. So you just kind of described how China might be thinking of it as a defensive slash offensive, basically a weapon for a potential, uh, conflict with the U.S., is that the same kind of thinking that Russia is doing? Or are they just, they seem more random? That's why I ask, because they seem more random in their attacks. 

[00:08:04] Amy Zegart: There are different flavors of their interests, right? So Russia is really focused on the disinformation space. So think about foreign election interference. So the Russians really like that space, uh, fomenting, uh, you know, exacerbating polarization in the United States. By the way, the Chinese are trying to do that too. The Iranians too, but Russia is the A team. That's, they're really good at that. The North Koreans want to steal. Right? So they're trying to steal everything they can in cyberspace. When you think about ransomware, I think primarily North Koreans, Russians too. 

[00:08:35] Russ Altman: Okay.

[00:08:35] Amy Zegart: But they're really in it for the money. The Iranians have sort of a vengeful attitude towards cyber attacks. So you'll see cyber attacks against, um, particular targets like casinos, right? And they're very vengeful, uh, in there, like specifically targeting, uh, you know, assets that are owned by people that say things that they don't like.

[00:08:58] Now that's a broad simplification of the differences between these four countries, but they're all very capable cyber adversaries. Uh, and those capabilities are growing over time. So it's a cat and mouse defense offense game. 

[00:09:13] Russ Altman: And can you update us on the issue of Russia? What have we learned from the Russian Ukrainian conflict? Has Russia, uh, have they been successful in kind of as part of their to include the cyber security or have the Ukrainians successfully fended them off? And are we learning anything by watching this conflict? Are we learning anything that could be useful to us in combating the Russians? 

[00:09:37] Amy Zegart: So yes and yes.

[00:09:38] Russ Altman: Okay, good. 

[00:09:39] Amy Zegart: Yes. Um, I think the narrative of the Russian cyber attacks against Ukraine at the start of the war turns out to be not quite right. You'll remember at the start of the war, the big question was, how come they didn't do more in cyberspace? They actually did do a lot in cyberspace, we now know, right?

[00:09:58] They attacked Viasat, so this is a pretty significant cyber attack. And they tried to do a lot more. Why didn't they succeed is the question, is the more important question. Part of the answer we now know is that United States Cyber Command was helping the Ukrainians weeks before the Russian attack.

[00:10:18] And so this was about moving critical digital assets to safer, uh, configurations. This was about fending off attacks. This was about working side by side with the Ukrainians to try to mitigate the risk of a cyber sort of first strike that would really take them out. And so we know a lot more now that's been revealed publicly about U.S. Cyber Command's role there. 

[00:10:40] The other thing I think that we learned is that cyber attacks in an ongoing conflict are actually really hard to pull off, right? So it's one thing to initiate an attack at the start of a conflict where you're planning to go in. 

[00:10:53] Russ Altman: The surprise. 

[00:10:54] Amy Zegart: But then sustaining that level of activity and adapting to the threat landscape turns out to be much harder.

[00:11:03] Russ Altman: Really interesting. Okay. So, um, all right. So you gave a great answer to my initial question. And the answer is that the cyber guys have gotten faster. The government is a little bit, is more on board and presumably is getting faster. Um, what about a domestic? I know that you've spent a lot of time thinking about, uh, global threats. Um, I think you also think about internal, um, domestic threats. Um, Is that true? 

[00:11:29] Amy Zegart: Not so much. I worry about things coming from outside the United States, not inside the United States. 

[00:11:35] Russ Altman: Okay. So tell me about, um, have they gotten, so misinformation, I want to talk about misinformation. Um, you already alluded to it as especially like messing up elections. Uh, and generally it's an attempt to create chaos. Is that how I should think about it? 

[00:11:52] Amy Zegart: So it depends. So let's just talk a little bit about terminology. So misinformation is information that is wrong, but people are mistakenly sending it around, right? So this is your crazy uncle sending things that he may think may be true, but are actually not true.

[00:12:08] So disinformation is a deliberate effort by somebody to spread something that they know to be false. We have both problems. People spreading things that are patently false, but they don't know they're false and they go viral. And then nefarious actors, domestic and foreign, that are knowingly spreading information that is false. 

[00:12:28] And in that category, right, there are a variety of motives, but from a foreign adversary perspective, it is to fray the bonds of democratic societies that bring us together. Anything that gets you and me to fight with each other about what's true or what's not, or what we believe in and, um, what our values are in conflict benefits these adversaries.

[00:12:50] Russ Altman: Yeah. So, and I've heard that. And so, you know, as you may be aware, Uh, there is a lot of splits in the U.S. right now, politically, and it makes me wonder when you say things like what you just said, um, is some of that manufactured not from deeply held beliefs of the two sides. Uh, but from external sources, and that would actually, in a funny way, be a hopeful thing, because it might imply that we actually have a chance to resolve some of these divides if we could kind of get the noise from the, uh, external pertur, perturbators out, but I don't know if that's too Pollyanna.

[00:13:25] I'm sure it is too Pollyannaish. So how should I think about when I look at the political divides in the U.S.? Do we have a sense for how much is that created from external sources and how much is in some sense? Like real, or is that not even a question that makes sense? 

[00:13:39] Amy Zegart: I think it's a great question. I don't think we know the answer. It's so hard to unravel what are the roots of, uh, the particular information that's being spread. Now there are researchers that are trying to do this, but that they're caught in the political maw as well, right? Seen as either censoring or favoring one side or the other. It's a really hard thing to unwind.

[00:14:00] And of course our adversaries are getting better at it and hiding their tracks. So you think back to, you know, Russia's early efforts to interfere with a presidential election. And, uh, we may have talked about this in the last time I came on. You know, you could easily trace it back after the fact to Facebook groups that were created by Prigozhin in St. Petersburg in an office with trolls that, you know, came to work nine to five and they masqueraded as Americans trying to get followers and getting Americans to be pitted against each other. Not just online, but in real life, right? On the streets of Texas, protesting against each other, all fomented by the Kremlin.

[00:14:40] Now it's a lot harder. And, you know, you think about TikTok, for example, the Chinese don't need the Russian playbook, which is utilize American platforms against ourselves. They have their own platform. Directly into the hands of forty percent of Americans, which is why there's been this whole bruhaha about banning TikTok or forcing a sale of TikTok. It is a legitimate national security concern. 

[00:15:04] Russ Altman: Great. Okay. Now there's something juicy and meaty we can talk about. So there are these big tech companies and uh, TikTok is a great example because I have graduate students who are ready to hit the streets in protest if, uh, if TikTok is shut down, because it evidently has become a huge part of their life. Um, so talk to me about your perception of the real risks of TikTok, uh, versus kind of manufactured political rhetoric that you think is not so beefy. 

[00:15:35] Amy Zegart: So I will say, and I mentioned this to General Nakasone when he was the head of Cyber Command and the National Security Agency, that, um, we were talking about our kids, I said, you know, I have a college daughter, and she runs her team's TikTok page, right?

[00:15:47] Russ Altman: Right, exactly. There you go. 

[00:15:49] Amy Zegart: How do you, and you know, and I had to send a note to the parents saying, hey, if you want to know what your kids are up to on TikTok, uh, you can take a look, but I have to tell you it's a national security threat. 

[00:16:00] Russ Altman: Oh my god. Oh, what a great message that would have been to get.

[00:16:03] Amy Zegart: So it was a bit of an awkward position to be in. So yes, I hear what you're saying, particularly young people, they get their news from TikTok. TikTok is a very big part of their life. So why do we care so much? 

[00:16:15] Russ Altman: They'll ask me, what's email? What's Instagram? Facebook is for my grandmother. It's all about TikTok. And they also say, just be, sorry to interrupt you. They also say, and these are my technical students, my computer science, or they say that we don't know how their algorithm works, but it is light years better than all the other algorithms in terms of putting things in front of me that I find interesting.

[00:16:37] Amy Zegart: Yeah. And by the way, that's one of the reasons China may not want to actually divest TikTok to an American buyer because they don't want that IP, that algorithm to be in foreign hands. 

[00:16:49] Russ Altman: Yes, it seems to be magically good. 

[00:16:50] Amy Zegart: So this dilemma, the U.S. is trying to force a sale. China doesn't want to sell. It's going to be very interesting to see what happens.

[00:16:57] But back to your question about what's the real national security concern about TikTok? There are several. Number one, access to data. So TikTok executives have been saying, no, no, no, no, no. There's a firewall between American data and Chinese access to the data. That is not true. Right? We know empirically that is not true.

[00:17:17] So data on a hundred and seventy million Americans can be accessible by Chinese owners of this company. And we know the national security law in China mandates that companies turn over data when asked. 

[00:17:31] Russ Altman: Is this data generated within the app or is this even other stuff on your phone that can be grabbed? 

[00:17:37] Amy Zegart: That I don't know.

[00:17:39] Russ Altman: Okay, but it's at least what I'm watching on TikTok, what I'm typing into TikTok, maybe where I am, if there's geolocation. I don't know if there's geolocation on TikTok. 

[00:17:48] Amy Zegart: So let me put it to you this way, Russ. Imagine the U.S. government had the ability to reach into the phones of forty percent of citizens in China. And know with the algorithm what gets their attention, what they like and what they don't. How much would we pay to have that kind of access to the populace of a foreign country?

[00:18:10] Russ Altman: And that's what they have. 

[00:18:11] Amy Zegart: That's what they have, right? That's what our kids and your students have. So that's issue number one is access to the data.

[00:18:19] Number two is influence. So it doesn't have to be a heavy handed, the Chinese Communist Party is great kind of TikTok algorithm, right? Where you're, you know, the viewers or my daughter is suddenly watching this. It can be things at the margin, right? You probably saw the story about Osama Bin Laden really had legitimate grievances when he masterminded the nine eleven attack.

[00:18:42] Just horrifying things. But on TikTok, this messaging went viral. Now, I don't know whether this was deliberately put there, right, by, in a deliberate effort by a foreign adversary, but you can see how ideas, if a government wanted to influence opinion on issues, uh, it would be pretty easy to do. 

[00:19:03] Russ Altman: Yeah, and your point is a really good one, that these can be nudges and not bludgeons.

[00:19:07] Amy Zegart: Right. 

[00:19:08] Russ Altman: And actually nudges are probably more insidious and difficult to find and are way less detectable. 

[00:19:15] Amy Zegart: That's a better way of putting it than what I just said. Yes. 

[00:19:17] Russ Altman: This is The Future of Everything. I'm Russ Altman. We'll have more with Amy Zegart next.

[00:19:36] Welcome back to The Future of Everything. I'm Russ Altman, your host, and I'm speaking with Amy Zegart from Stanford University. 

[00:19:42] In the last segment, Amy described to us some of the changes that have happened since we last spoke with her in cybersecurity threat assessment and also response. In this segment, we're going to talk about the role of corporations. They have more compute power, not only more than academics. In many cases, they have more than the government has to use in building AI tools. This has created new challenges for regulation and for collaboration between industry and government and academics. 

[00:20:11] Amy, to start off this segment, I wanted to ask you about the role of corporations. We talked about it a tiny bit when we're talking about the SEC regulations, but there are these big tech companies that are really holding AI and controlling AI. What is the role of the corporation in national security these days? 

[00:20:28] Amy Zegart: Well Russ, the role of the corporation is totally different than it was when we were growing up. So it used to be that innovations were invented in the government and then they became commercialized, right? You think about the internet started that way, or GPS satellites. And now the script has flipped. So now innovations, and we see this with large language models, are being invented outside of the government, and the government has to figure out not only what to do about that in the private sector, but how to bring those capabilities into the government itself.

[00:20:57] That's a new world for them. We're in a world right now where a handful of companies really dwarf the capacity of the government or universities to, uh, to compete and understand these large language models. 

[00:21:12] Russ Altman: And there is no way that me and my friends could have built ChatGPT. We don't have a tenth of the compute power we would need.

[00:21:21] Amy Zegart: And I think Russ, many people don't know that, right? So the orders of magnitude of compute power, right? So how much more compute power does OpenAI have than Stanford, for example? I mean, you know, it's, you know, you probably don't have, 

[00:21:37] Russ Altman: It's ten to a hundred, it's a hundred X. It's a hundred X. 

[00:21:40] Amy Zegart: So I was trying to find a specific number cause I'm writing about this now. And I saw an announcement that Princeton is buying, is very excited, that they're buying three hundred NVIDIA chips by the end of the year. Meta is expected to have three hundred and fifty thousand, right? So, 

[00:21:59] Russ Altman: So it's a thousand X. I was off by an order of magnitude. You're right. 

[00:22:03] Amy Zegart: And so what that means is that these companies are not just at the forefront of innovating, they're grading their own homework, right? Because how do you know what's safe? How do you know what potential risks there are? What kinds of questions do you need to ask? They're deciding those things largely by themselves, and that's never a good setup. I would say that, but I also want to emphasize that we don't want to impede innovation.

[00:22:26] So the question is, how do you strike the right balance between mitigating harms from these AI models. And how do you make sure that we're allowing the private sector leaders in this space, and they are all American at this moment, to continue innovating in ways that help, you know, there's so many positive benefits to these models as well. So we don't want to impede that either. 

[00:22:47] Russ Altman: So what is the approach? I mean, is it now requiring government to have some kind of super awkward type of conversations that it's not used to having where it's kind of, it has to be a little bit more humble, perhaps, and come to the companies and say, hey, could we work together?

[00:23:04] I mean, first of all, I presume that they're a part of the national security infrastructure. We would want to use many of those technologies to combat, uh, threats. On the other hand, um, they're not under the control of the government and they might say things like, who's going to pay for that? Or, you know, how much should the license that the government pays us, how much should that cost? And so, how far are we at figuring out how this new dance should be danced? 

[00:23:30] Amy Zegart: Well, you know, we just talked about cyber and how long it took to sort of get the maturation of cyber organization in the U.S. government. We're on day one for AI. So we are not far along at all. Yes, there are awkward conversations. You can see them on television when Sam Altman goes to testify before Congress. You know, many members of Congress are learning how to spell AI. So we have a, we have an expertise challenge there too. So at one point I counted the number of members of Congress that had engineering degrees. I think it was in 2020.

[00:24:00] You will be unsurprised to know more than half the Senate had law degrees. And there were, I think, three engineers. Which is actually more than I thought there would be. So that's part of the challenge too, is, you know, ordinary folks don't know enough to be able to ask the right oversight questions. 

[00:24:16] Russ Altman: So here's overly optimistic Russ's next question. Did we learn from cyber so many lessons that AI is going to be easier? Based on the cyber experience, or are we basically starting from scratch? 

[00:24:28] Amy Zegart: I think I'm trying to be optimistic. I'm trying to get your optimism, Russ. Yes, we have learned some lessons. You can see efforts early on at conversation, both on the private sector side. They know they've got this powerful technology and they're concerned about the risks. I don't want to overstate. 

[00:24:45] Russ Altman: They want to be patriots to some degree, I would guess, slash hope. 

[00:24:49] Amy Zegart: And they know that what they have has great promise and also great peril and trying to harness the upside while mitigating the downside is in everybody's interest.

[00:24:58] So those conversations are happening. We don't have the Edward Snowden problem. So you remember in 2013, former NSA contractor revealed highly classified programs, and it really sowed distrust, deep distrust between companies here in the Valley and the government. We don't have that right now. 

[00:25:15] Thanks to Xi Jinping and Vladimir Putin there's a joint concern about authoritarians in the world and the bad they can do. So that's good. We have learned from that, but you know, there is this question of what do we do, given that there's just this capacity differential between talent and compute and algorithms and a handful of companies and what everybody else can do.

[00:25:38] And I think we have three options. One is regulation. I'm concerned about that because you can really, you know, uh, throw the baby out with the bath water. Two is do nothing, let them grade their own homework. That concerns me too. What happens if, uh, people violate OpenAI's rules in the presidential election? They, they go to OpenAI jail, right? I mean, it's voluntary compliance. 

[00:25:59] Russ Altman: No chat for you. 

[00:26:01] Amy Zegart: So that's the world we're in right now. And then the third option, I think this is what we really need to pursue much more seriously is developing independent capacity. Developing the talent, developing the compute thing.

[00:26:15] I know Stanford's been really pushing this idea of a national AI research resource. That's fancy talk for compute power so that independent researchers can ask hard questions, uh, and do the kind of analysis that, that needs to be done. I think we need to be investing much more in that. Compute is a strategic national asset like oil and the government should be investing orders of magnitude more and making that available.

[00:26:44] Russ Altman: You know, as a biomedical researcher, I'm very aware of this because whenever, for example, the drug industry gets out ahead of NIH researchers, the NIH has a history, and I've seen this several times in my career, of making huge investments to try to level the playing field so that academic can kind of not really compete with the pharmaceutical industry. But do things at the same scale. 

[00:27:05] And I'm somewhat surprised to not have seen a government scale, uh, AI resource that's as big as Facebook's or OpenAIs or Anthropics or, it's just surprising because the government can definitely afford it. Yes, it's expensive, but you know, the government has a bigger budget than Facebook even and so it's just surprising and maybe we'll see this.

[00:27:27] Um, let me just ask you, you mentioned about regulation. I'm sure you have opinions about the Europeans. As you know, the Europeans have been very aggressive at um, kind of AI and data protections. What's your take on that in terms of the security implications? Is that a model that the U.S. should seriously look at? Or do you have concerns about how they've approached it? 

[00:27:47] Amy Zegart: I understand where they're coming from, and the Europeans share our values. And so I think that the impetus, I understand. I think their hearts in the right place, but I don't think it's a coincidence that the leading AI companies in the world are not coming out of Europe.

[00:28:01] They're coming out of the United States. Our, you know, wild west approach to innovation, hands off regulation is both a feature and a bug, right? It is what is fostering this innovation explosion that we've had for a long time. But it also means that we have a harder time mitigating the harms. So what I think is most promising and what the Europeans have done, two things.

[00:28:26] One is starting an international conversation about norms. That's really important. Ultimately, I think that we also need a serious bilateral conversation about AI guardrails between the U.S. and China. Things like AI and nuclear command and control, AI and financial system security, things where we have mutual interests, we need to have that.

[00:28:48] But the multilateral approach is important, too, for building norms about what's acceptable and what isn't. The second thing the Europeans are doing is the UK has really taken the lead on their AI Safety Institute. Independent capacity building to really understand what the risks of this technology could be.

[00:29:06] Now it's a beginning, it's not an end. The United States is behind. We're behind in our organization. We're behind in our funding compared to the Brits. And as you probably know, now there's conversation about how can we join our efforts together. And I think that's very promising. 

[00:29:21] Russ Altman: Great. So to finish up. How is AI going to help intelligence? Like, I know that the bad guys might use AI as well, but what are some of the ways, like, kind of tangible ways that we should be excited about AI helping increase our security and safety? 

[00:29:36] Amy Zegart: So, I do think there is some good news of the potential of AI. So, it can help intelligence in a number of ways.

[00:29:43] First, you have to think about intelligence isn't really about secrets, it's about insight. So the question is, how can analysts sitting inside the Central Intelligence Agency better develop insight about what's going on around the world? Well, what can AI do? AI can do pattern recognition at scale and speeds that humans cannot.

[00:30:02] So you think about an analyst, there was actually an experiment done several years ago by the National Geospatial Intelligence Agency. And they had a human team and an AI team looking at identifying surface to air missile sites over a huge swath of territory. The humans and the algorithms did the, had the same level of accuracy, ninety percent accuracy, but the AI did it eighty times faster.

[00:30:28] What does that mean? Now you're freeing up the human analysts to do things that only humans can do well, like thinking about intention. What does the adversary intend to do with those surface to air? 

[00:30:40] Russ Altman: Why are they pointing in that direction? 

[00:30:42] Amy Zegart: Why are they pointing in that direction? Yeah. So, so incredible efficiency gains, right?

[00:30:46] Pattern recognition. That's thing one. Thing two is AI can help find needles in haystacks. Much better than humans can pouring over images or pouring over data. And the third thing that AI can do, is AI can derive insight from the haystacks themselves. So I think about in your world, AI, um, accelerating scientific discovery, the new antibiotic at MIT, that's finding insight from mounds and mounds of data, all the haystacks, connections that humans didn't even know existed. AI can help with that. 

[00:31:23] Russ Altman: Thanks to Amy Zegart, that was The Future of Cybersecurity. Thanks for tuning into this episode. With over 250 episodes in our archive, you have instant access to an extensive array of fascinating discussions on the future of pretty much everything. Please remember to hit follow in the app that you're listening to now.

[00:31:41] This will guarantee that you never miss out on the future of anything. You can connect with me on x or twitter @rbaltman. You can connect with Stanford Engineering @stanfordeng.

Clayton Bates Jr., expert on photoelectronic materials and devices who worked to promote equity in STEM education, has died

• School News

Laying the foundation for today’s generative AI

John Hennessy to receive the National Science Board Vannevar Bush Award

Smart. Open. Grounded. Inventive. Read our Ideas Made to Matter.

Which program is right for you?

Through intellectual rigor and experiential learning, this full-time, two-year MBA program develops leaders who make a difference in the world.

A rigorous, hands-on program that prepares adaptive problem solvers for premier finance careers.

A 12-month program focused on applying the tools of modern data science, optimization and machine learning to solve real-world business problems.

Earn your MBA and SM in engineering with this transformative two-year program.

Combine an international MBA with a deep dive into management science. A special opportunity for partner and affiliate schools only.

A doctoral program that produces outstanding scholars who are leading in their fields of research.

Bring a business perspective to your technical and quantitative expertise with a bachelor’s degree in management, business analytics, or finance.

A joint program for mid-career professionals that integrates engineering and systems thinking. Earn your master’s degree in engineering and management.

An interdisciplinary program that combines engineering, management, and design, leading to a master’s degree in engineering and management.

Executive Programs

A full-time MBA program for mid-career leaders eager to dedicate one year of discovery for a lifetime of impact.

This 20-month MBA program equips experienced executives to enhance their impact on their organizations and the world.

Non-degree programs for senior executives and high-potential managers.

A non-degree, customizable program for mid-career professionals.

Categorical thinking can lead to investing errors

How storytelling helps data-driven teams succeed

Financial services’ deliberate approach to AI

Credit: Rob Dobi

Ideas Made to Matter

Cybersecurity

MIT report details new cybersecurity risks

Beth Stackpole

Apr 30, 2024

Despite rigorous security efforts by all organizations, cybercriminals are still finding new ways to exploit personal and business data. Data breaches increased by nearly 20% in the first nine months of 2023 compared with all of 2022, and ransomware attacks escalated by almost 70% in the same time frame.

In fact, data breaches hit an all-time high in 2023 — a trend fueled by increasing online interactions that put personal data in the crosshairs of criminal activity, according to MIT professor  Stuart Madnick.

Organizations aren’t unaware of heightened cybersecurity risks. In fact, cybersecurity has escalated from an IT-level discussion to a C-suite and boardroom issue, with worldwide spending on security and risk management projected to hit $215 billion in 2024, according to research firm Gartner. Yet hackers are finding more creative ways to bypass security measures, motivated by the troves of unencrypted personal data being collected and stored in enterprise systems, said Madnick, the co-founder and co-director of Cybersecurity at MIT Sloan .

Once hackers realize an organization is vulnerable to an attack, they will repeatedly attempt to breach its network, he said. In fact, 95% of organizations surveyed by IBM  between March 2022 and March 2023 said they had experienced more than one data breach.

“Most companies are aware of the threat and are doing things to improve security, but the bad guys haven’t stayed still either,” Madnick said. “You have to think beyond what you did for protection last year.”

In a new report , Madnick identifies three primary reasons behind the latest uptick in personal data theft: misconfiguration of cloud environments, the emergence of new and more dangerous types of ransomware, and increased exploitation of vendor systems (an attack vector sometimes referred to as a supply chain breach).

Three main cyberattack vectors

Madnick and his team have identified three scenarios contributing to the recent increases in the frequency and impact of personal data breaches.

More than 80% of data breaches involved data stored in the cloud, according to a 2023 report.

Cloud misconfiguration. Companies have been migrating data and core systems to the cloud in droves, to the point where an estimated 60% of corporate data now resides in the cloud. Yet the technology is still evolving, and many IT organizations don’t have employees experienced in the nuances of the cloud configurations and procedures required to properly secure data. According to the IBM survey, more than 80% of data breaches involved data stored in the cloud. Cloud misconfigurations, such as failure to change default settings, unrestricted ports, and unsecured backups, are just some ways hackers are gaining access to cloud-based data and services, Madnick said.

Organizations can mitigate misconfiguration vulnerabilities by addressing security early in the build cycle of systems, hiring or developing the right talent and skill sets to configure a dynamic cloud environment, and conducting proper audits and monitoring.

The evolving and growing threat of ransomware. Ransomware attacks, where hackers take control of institutional data and demand a ransom in exchange for its return, have become more common and are changing in nature. Historically, companies hit by ransomware faced operational outages and had their corporate data locked up. Today, it’s become standard for bad actors to also steal personal data collected and stored by organizations, and to take aggressive actions such as threatening to leak stolen consumer data on the dark web — essentially adding blackmail to their ransom attacks.

Madnick said that more sophisticated ransomware techniques, including those incorporating artificial intelligence and cooperative efforts by ransomware gangs, are contributing to the rise in ransomware attacks. Ransomware-as-a-service, essentially a “productized” version of malware that’s available to bad actors, is also driving up attacks.

Diligent data backup and restore practices remain important protection tools for corporate data. Organizations also need to monitor for and stop any data exfiltration from internal systems and embrace encryption practices so stored data is not useful to attackers, Madnick said.

Vendor exploitation attacks. All the vendor-provided mission-critical accounting, inventory, and customer management systems used by companies also offer a way into corporate systems (something Madnick refers to as a “side door”). These side doors allow vendors to provide regular updates and patches, but attackers can exploit vulnerabilities in the vendor’s systems to reach customers using those services — a vector known as a supply chain attack.  

Related Articles

A single unpatched vulnerability in one vendor’s software allows hackers to gain access to the personal data of many organizations across the globe that use that vendor’s software. In one example cited in Madnick’s report, hackers exploited a vulnerability in the MOVEit managed file transfer software that affected over 2,300 companies in more than 30 countries. As a result, more than 65 million individuals’ data had been compromised as of October 2023.

To avoid or minimize damage from this scenario, Madnick recommends using specialized companies to evaluate the cybersecurity health of any vendor being considered as a partner. It’s also important to take steps to minimize vendors’ side-door capabilities by limiting their access to only what’s required.

Other recommendations for companies from the report include the following:

• Limit the amount of personal data stored in a readable format.
• Adopt solutions that implement end-to-end encryption to reduce the amount of stored vulnerable data that presents risks to individuals.
• Don’t be an ostrich — acknowledge the severity of the current landscape, invest in the right tools, and educate the broader employee base on cybersecurity responsibilities accordingly.

“There’s very little you can do to guarantee you’re not a victim, but there are a lot of things you can do to be more secure that aren’t being done,” Madnick said.

Read the report: “The Continued Threat to Personal Data — Key Factors Behind the 2023 Increase”

Suggestions or feedback?

MIT News | Massachusetts Institute of Technology

• Machine learning
• Social justice
• Black holes
• Classes and programs

Departments

• Aeronautics and Astronautics
• Brain and Cognitive Sciences
• Architecture
• Political Science
• Mechanical Engineering

Centers, Labs, & Programs

• Abdul Latif Jameel Poverty Action Lab (J-PAL)
• Picower Institute for Learning and Memory
• Lincoln Laboratory
• School of Architecture + Planning
• School of Engineering
• School of Humanities, Arts, and Social Sciences
• Sloan School of Management
• School of Science
• MIT Schwarzman College of Computing

HPI-MIT design research collaboration creates powerful teams

Press contact :.

Previous image Next image

The recent ransomware attack on ChangeHealthcare, which severed the network connecting health care providers, pharmacies, and hospitals with health insurance companies, demonstrates just how disruptive supply chain attacks can be. In this case, it hindered the ability of those providing medical services to submit insurance claims and receive payments. This sort of attack and other forms of data theft are becoming increasingly common and often target large, multinational corporations through the small and mid-sized vendors in their corporate supply chains, enabling breaks in these enormous systems of interwoven companies. Cybersecurity researchers at MIT and the Hasso Plattner Institute (HPI) in Potsdam, Germany, are focused on the different organizational security cultures that exist within large corporations and their vendors because it’s that difference that creates vulnerabilities, often due to the lack of emphasis on cybersecurity by the senior leadership in these small to medium-sized enterprises (SMEs). Keri Pearlson, executive director of Cybersecurity at MIT Sloan (CAMS); Jillian Kwong, a research scientist at CAMS; and Christian Doerr, a professor of cybersecurity and enterprise security at HPI, are co-principal investigators (PIs) on the research project, “Culture and the Supply Chain: Transmitting Shared Values, Attitudes and Beliefs across Cybersecurity Supply Chains.”

Their project was selected in the 2023 inaugural round of grants from the HPI-MIT Designing for Sustainability program , a multiyear partnership funded by HPI and administered by the MIT Morningside Academy for Design (MAD). The program awards about 10 grants annually of up to $200,000 each to multidisciplinary teams with divergent backgrounds in computer science, artificial intelligence, machine learning, engineering, design, architecture, the natural sciences, humanities, and business and management. The 2024 Call for Applications is open through June 3. Designing for Sustainability grants support scientific research that promotes the United Nations’ Sustainable Development Goals (SDGs) on topics involving sustainable design, innovation, and digital technologies, with teams made up of PIs from both institutions. The PIs on these projects, who have common interests but different strengths, create more powerful teams by working together.

Transmitting shared values, attitudes, and beliefs to improve cybersecurity across supply chains

The MIT and HPI cybersecurity researchers say that most ransomware attacks aren’t reported. Smaller companies hit with ransomware attacks just shut down, because they can’t afford the payment to retrieve their data. This makes it difficult to know just how many attacks and data breaches occur. “As more data and processes move online and into the cloud, it becomes even more important to focus on securing supply chains,” Kwong says. “Investing in cybersecurity allows information to be exchanged freely while keeping data safe. Without it, any progress towards sustainability is stalled.”

One of the first large data breaches in the United States to be widely publicized provides a clear example of how an SME cybersecurity can leave a multinational corporation vulnerable to attack. In 2013, hackers entered the Target Corporation’s own network by obtaining the credentials of a small vendor in its supply chain: a Pennsylvania HVAC company. Through that breach, thieves were able to install malware that stole the financial and personal information of 110 million Target customers, which they sold to card shops on the black market.

To prevent such attacks, SME vendors in a large corporation’s supply chain are required to agree to follow certain security measures, but the SMEs usually don’t have the expertise or training to make good on these cybersecurity promises, leaving their own systems, and therefore any connected to them, vulnerable to attack.

“Right now, organizations are connected economically, but not aligned in terms of organizational culture, values, beliefs, and practices around cybersecurity,” explains Kwong. “Basically, the big companies are realizing the smaller ones are not able to implement all the cybersecurity requirements. We have seen some larger companies address this by reducing requirements or making the process shorter. However, this doesn’t mean companies are more secure; it just lowers the bar for the smaller suppliers to clear it.”

Pearlson emphasizes the importance of board members and senior management taking responsibility for cybersecurity in order to change the culture at SMEs, rather than pushing that down to a single department, IT office, or in some cases, one IT employee.

The research team is using case studies based on interviews, field studies, focus groups, and direct observation of people in their natural work environments to learn how companies engage with vendors, and the specific ways cybersecurity is implemented, or not, in everyday operations. The goal is to create a shared culture around cybersecurity that can be adopted correctly by all vendors in a supply chain.

This approach is in line with the goals of the Charter of Trust Initiative, a partnership of large, multinational corporations formed to establish a better means of implementing cybersecurity in the supply chain network. The HPI-MIT team worked with companies from the Charter of Trust and others last year to understand the impacts of cybersecurity regulation on SME participation in supply chains and develop a conceptual framework to implement changes for stabilizing supply chains.

Cybersecurity is a prerequisite needed to achieve any of the United Nations’ SDGs, explains Kwong. Without secure supply chains, access to key resources and institutions can be abruptly cut off. This could include food, clean water and sanitation, renewable energy, financial systems, health care, education, and resilient infrastructure. Securing supply chains helps enable progress on all SDGs, and the HPI-MIT project specifically supports SMEs, which are a pillar of the U.S. and European economies.

Personalizing product designs while minimizing material waste

In a vastly different Designing for Sustainability joint research project that employs AI with engineering, “Personalizing Product Designs While Minimizing Material Waste” will use AI design software to lay out multiple parts of a pattern on a sheet of plywood, acrylic, or other material, so that they can be laser cut to create new products in real time without wasting material.

Stefanie Mueller, the TIBCO Career Development Associate Professor in the MIT Department of Electrical Engineering and Computer Science and a member of the Computer Science and Artificial Intelligence Laboratory, and Patrick Baudisch, a professor of computer science and chair of the Human Computer Interaction Lab at HPI, are co-PIs on the project. The two have worked together for years; Baudisch was Mueller’s PhD research advisor at HPI.

Baudisch’s lab developed an online design teaching system called Kyub that lets students design 3D objects in pieces that are laser cut from sheets of wood and assembled to become chairs, speaker boxes, radio-controlled aircraft, or even functional musical instruments. For instance, each leg of a chair would consist of four identical vertical pieces attached at the edges to create a hollow-centered column, four of which will provide stability to the chair, even though the material is very lightweight.

“By designing and constructing such furniture, students learn not only design, but also structural engineering,” Baudisch says. “Similarly, by designing and constructing musical instruments, they learn about structural engineering, as well as resonance, types of musical tuning, etc.”

Mueller was at HPI when Baudisch developed the Kyub software, allowing her to observe “how they were developing and making all the design decisions,” she says. “They built a really neat piece for people to quickly design these types of 3D objects.” However, using Kyub for material-efficient design is not fast; in order to fabricate a model, the software has to break the 3D models down into 2D parts and lay these out on sheets of material. This takes time, and makes it difficult to see the impact of design decisions on material use in real-time.

Mueller’s lab at MIT developed software based on a layout algorithm that uses AI to lay out pieces on sheets of material in real time. This allows AI to explore multiple potential layouts while the user is still editing, and thus provide ongoing feedback. “As the user develops their design, Fabricaide  decides good placements of parts onto the user's available materials, provides warnings if the user does not have enough material for a design, and makes suggestions for how the user can resolve insufficient material cases,” according to the project website.

The joint MIT-HPI project integrates Mueller’s AI software with Baudisch’s Kyub software and adds machine learning to train the AI to offer better design suggestions that save material while adhering to the user’s design intent.

“The project is all about minimizing the waste on these materials sheets,” Mueller says. She already envisions the next step in this AI design process: determining how to integrate the laws of physics into the AI’s knowledge base to ensure the structural integrity and stability of objects it designs.

AI-powered startup design for the Anthropocene: Providing guidance for novel enterprises

Through her work with the teams of MITdesignX and its international programs, Svafa Grönfeldt, faculty director of MITdesignX and professor of the practice in MIT MAD, has helped scores of people in startup companies use the tools and methods of design to ensure that the solution a startup proposes actually fits the problem it seeks to solve. This is often called the problem-solution fit.

Grönfeldt and MIT postdoc Norhan Bayomi are now extending this work to incorporate AI into the process, in collaboration with MIT Professor John Fernández and graduate student Tyler Kim. The HPI team includes Professor Gerard de Melo; HPI School of Entrepreneurship Director Frank Pawlitschek; and doctoral student Michael Mansfeld.

“The startup ecosystem is characterized by uncertainty and volatility compounded by growing uncertainties in climate and planetary systems,” Grönfeldt says. “Therefore, there is an urgent need for a robust model that can objectively predict startup success and guide design for the Anthropocene.”

While startup-success forecasting is gaining popularity, it currently focuses on aiding venture capitalists in selecting companies to fund, rather than guiding the startups in the design of their products, services and business plans.

“The coupling of climate and environmental priorities with startup agendas requires deeper analytics for effective enterprise design,” Grönfeldt says. The project aims to explore whether AI-augmented decision-support systems can enhance startup-success forecasting.

“We're trying to develop a machine learning approach that will give a forecasting of probability of success based on a number of parameters, including the type of business model proposed, how the team came together, the team members’ backgrounds and skill sets, the market and industry sector they're working in and the problem-solution fit,” says Bayomi, who works with Fernández in the MIT Environmental Solutions Initiative. The two are co-founders of the startup Lamarr.AI, which employs robotics and AI to help reduce the carbon dioxide impact of the built environment.

The team is studying “how company founders make decisions across four key areas, starting from the opportunity recognition, how they are selecting the team members, how they are selecting the business model, identifying the most automatic strategy, all the way through the product market fit to gain an understanding of the key governing parameters in each of these areas,” explains Bayomi.

The team is “also developing a large language model that will guide the selection of the business model by using large datasets from different companies in Germany and the U.S. We train the model based on the specific industry sector, such as a technology solution or a data solution, to find what would be the most suitable business model that would increase the success probability of a company,” she says.

The project falls under several of the United Nations’ Sustainable Development Goals, including economic growth, innovation and infrastructure, sustainable cities and communities, and climate action.

Furthering the goals of the HPI-MIT Joint Research Program

These three diverse projects all advance the mission of the HPI-MIT collaboration. MIT MAD aims to use design to transform learning, catalyze innovation, and empower society by inspiring people from all disciplines to interweave design into problem-solving. HPI uses digital engineering concentrated on the development and research of user-oriented innovations for all areas of life.

Interdisciplinary teams with members from both institutions are encouraged to develop and submit proposals for ambitious, sustainable projects that use design strategically to generate measurable, impactful solutions to the world’s problems.

Share this news article on:

Related links.

• Cybersecurity at MIT Sloan
• MIT Morningside Academy for Design
• Hasso Plattner Institute

Related Topics

• Manufacturing
• Collaboration
• Supply chains
• Cybersecurity
• Business and management
• Artificial intelligence
• Climate change
• Cleaner industry
• Renewable energy
• Electrical Engineering & Computer Science (eecs)
• Innovation and Entrepreneurship (I&E)
• Computer Science and Artificial Intelligence Laboratory (CSAIL)
• Environmental Solutions Initiative
• MIT Sloan School of Management
• School of Architecture and Planning

Related Articles

A new way to integrate data with physical objects

New research collaboration aims to tackle global societal challenges through design

MIT Morningside Academy for Design created as a new hub for cross-disciplinary education, research, and innovation

Previous item Next item

More MIT News

President Sally Kornbluth and OpenAI CEO Sam Altman discuss the future of AI

Read full story →

MIT astronomers observe elusive stellar light surrounding ancient quasars

Creating bespoke programming languages for efficient visual AI systems

MIT conductive concrete consortium cements five-year research agreement with Japanese industry

One of MIT’s best-kept secrets lives in the Institute’s basement

Exploring frontiers of mechanical engineering

• More news on MIT News homepage →

Massachusetts Institute of Technology 77 Massachusetts Avenue, Cambridge, MA, USA

• Map (opens in new window)
• Events (opens in new window)
• People (opens in new window)
• Careers (opens in new window)
• Accessibility
• Social Media Hub
• MIT on Facebook
• MIT on YouTube
• MIT on Instagram

An official website of the United States government

Here’s how you know

Official websites use .gov A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS A lock ( Lock A locked padlock ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

• Science and Technology Directorate

Feature Article: Digital Mapping Helps First Responders Better Navigate Inside Buildings

Agencies are using S&T-funded Mappedin to find their way quickly during critical incidents in schools and public buildings.

GPS systems may get first responders to incident scenes fast, but navigating buildings’ complex mazes of hallways and corridors in potentially chaotic or low-visibility situations can be tricky. Relying on hard copy or digital building blueprints can be cumbersome or even outdated, adding precious seconds when time is of the essence.

A solution, brought to you by the Science and Technology Directorate (S&T) and digital indoor map navigator Mappedin, was completed in 2022 and has since flourished. The online Mappedin mapmaking subscription, which can transform floor plans into interactive and easily maintainable digitized maps, was recently launched and is currently being used by both response agencies and corporate clients. With easy-to-use mapping tools and data, Mappedin provides high-quality 3D map creation, data maintenance, and map sharing to city executives, building owner operators and first responders to make and deliver maps for a variety of safety-related situations—from advance preparation and planning to assistance during emergency incidents.

“With Mappedin, first responders can quickly determine the interior layout of structures before entering a building to make informed decisions,” said Anthony Caracciolo, the S&T program manager who led this effort. “Mappedin assists them with identifying where interior rooms, doors, stairs, key equipment and hazardous materials are located and enables them to possess indoor awareness of a facility before entering.”

Mappedin provides intelligent digitization of floor plans from various sources (e.g., computer-aided design drawings, PDF documents, photographs) and maintains a digital reserve of 3D interactive maps accessible on tablets and cell phones. These maps can be marked up and shared via a private link accessible only to authorized personnel.

To save time in mapmaking, Mappedin leverages artificial intelligence (AI) to create high-quality 3D interactive indoor maps from uploaded floor plan images in 0.5 minutes to 3 minutes. The tool also uses LiDAR, a remote sensing method, to create floor plans from scratch. With an iPhone Pro or iPad Pro and the Mappedin iOS app, users can scan their indoor environment and turn the data into a digital map, which they can further edit and customize by labeling specific rooms and areas and adding attributes such as descriptions, photographs and links.

S&T initially funded Mappedin Inc. in 2019 to develop the indoor mapping tool (then called Response) after S&T's First Responder Resource Group indicated this type of technology was a top need. S&T’s goal was to help responders quickly navigate indoor floor plans in real-time when responding to incidents. Mappedin enables point-to-point wayfinding, like an indoor GPS, and is available to first responders and local governments as a licensed cloud-based service. S&T and Mappedin demonstrated the software in 2022 , when first responders assessed the prototype’s efficiency and recommended improvements before commercialization. First responders found it better than existing technologies and liked its compatibility with many existing software platforms. Then, S&T and Mappedin further improved the software based on feedback from U.S. and Canadian first responders and local governments.

Public schools and fire departments are among users

Mappedin is already in use successfully. Since its official launch in September 2023, more than 4,000 user accounts have been created.  

Many of Mappedin’s new customers are public schools and fire departments for whom mapping services are free. To provide life-saving technology to schools and first responders, two former firefighters have integrated Mappedin maps into their school safety product, AIKI ClassroomSAFE. The app provides situational awareness and a comprehensive view of other responding agencies, students, and the real-time status of classrooms. According to experienced firefighter and AIKI co-founder, Damian McKeon, Mappedin has taken a multi-hour mapping process down to a couple of minutes.

Some forward-thinking schools in the U.S. and Canada are also looking to use Mappedin. Three pilot Canadian cities–Orangeville, Kitchener and Waterloo–have already adopted the tool to digitize paper floor plans for a variety of building types for pre-planning and educational purposes.

Also, first responders in 911 incident dispatch will be able to access Mappedin-created maps within their safety platform for precise geolocation. By providing Mappedin’s accurate geo-located annotations of key safety equipment before the trucks arrive on scene, the 911 dispatch can be prioritized as the first point of contact. According to Dain Bolling, Founder of Pure Wireless LLC, Mappedin easily creates spatially accurate maps suitable for first responders during critical incidents.

Moreover, efforts are underway to map an entire Florida county. Mappedin is accelerating its Maps for Good initiative to address the needs of schools and first responders. Eligible participants will receive no- to low-cost indoor mapping. “Indoor maps are crucial for situational awareness in built environments, and Mappedin is proud to be part of the solution,” said Hongwei Liu, co-founder and CEO at Mappedin. “With Maps for Good, we’re putting AI-powered indoor mapping directly into the hands of front-line professionals, giving them purpose-built tools to do their jobs and keep people safe.”

Mappedin could be integrated with other tools

The Mappedin free subscription is available for schools and responders, where anyone is encouraged to create their own maps. The paid Plus subscription, released in February 2024, and the Pro subscription, coming later this year, add advanced capabilities, including integration with other tools.

“One such possible integration is with the S&T-developed gunshot detection system that detects and alerts police of gunshots,” said Caracciolo. “If integrated with Mappedin, police would not only be alerted of the gunshots, but they could also receive an interior map of a building depicting where the gunshots are occurring, thus enabling police officers to engage the shooter and locate and start treating victims as soon as possible.”

Additionally, corporate customers, such as airports, stadiums, and office buildings are also using Mappedin for things like complex mapping, wayfinding, and custom integrations.

“Ultimately,” Caracciolo added, “S&T invested in Mappedin to equip first responders with the best tool to pre-plan and navigate building interiors in emergencies.”  

Learn more about S&T’s innovative industry partnerships and support for the nation’s first responders . For related media inquiries, contact [email protected] .

• Science and Technology
• First Responders
• Public Safety