Outputs (49)

Digital twins in industry 4.0 cyber security (2024)
Conference Proceeding
Lo, C., Win, T. Y., Rezaeifar, Z., Khan, Z., & Legg, P. (2024). Digital twins in industry 4.0 cyber security. In Proceedings of the IEEE Smart World Congress 2023. https://doi.org/10.1109/swc57546.2023.10449147

The increased adoption of sophisticated Cyber Physical Systems (CPS) in critical infrastructure and various aspects of Industry 4.0 has exposed vulnerabilities stemming from legacy CPS and Industrial Internet of Things (IIoT) devices. The interconnec... Read More about Digital twins in industry 4.0 cyber security.

Federated learning: Data privacy and cyber security in edge-based machine learning (2023)
Book Chapter
White, J., & Legg, P. (2023). Federated learning: Data privacy and cyber security in edge-based machine learning. In C. Hewage, Y. Rahulamathavan, & D. Ratnayake (Eds.), Data Protection in a Post-Pandemic Society (DPPPS) – Best Practices, Laws, Regulations, and Recent Solutions. Springer. https://doi.org/10.1007/978-3-031-34006-2

Machine learning is now a key component of many applications for understanding trends and characteristics within the wealth of data that may be processed, whether this be learning about customer preferences and travel preferences, forecasting future... Read More about Federated learning: Data privacy and cyber security in edge-based machine learning.

Teaching offensive and defensive cyber security in schools using a Raspberry Pi Cyber Range (2023)
Journal Article
Legg, P., Mills, A., & Johnson, I. (2023). Teaching offensive and defensive cyber security in schools using a Raspberry Pi Cyber Range. Journal of The Colloquium for Information Systems Security Education, 10(1), 9. https://doi.org/10.53735/cisse.v10i1.172

Computer Science as a subject is now appearing in more school curricula for GCSE and A level, with a growing demand for cyber security to be embedded within this teaching. Yet, teachers face challenges with limited time and resource for preparing pra... Read More about Teaching offensive and defensive cyber security in schools using a Raspberry Pi Cyber Range.

Interactive cyber-physical system hacking: Engaging students early using scalextric (2023)
Journal Article
White, J., Legg, P., & Mills, A. (2023). Interactive cyber-physical system hacking: Engaging students early using scalextric. Journal of The Colloquium for Information Systems Security Education, 10(1), 6. https://doi.org/10.53735/cisse.v10i1.163

Cyber Security as an education discipline covers a variety of topics that can be challenging and complex for students who are new to the subject domain. With this in mind, it is crucial that new students are motivated by understanding both the techni... Read More about Interactive cyber-physical system hacking: Engaging students early using scalextric.

Defending against adversarial machine learning attacks using hierarchical learning: A case study on network traffic attack classification (2022)
Journal Article
McCarthy, A., Ghadafi, E., Andriotis, P., & Legg, P. (2023). Defending against adversarial machine learning attacks using hierarchical learning: A case study on network traffic attack classification. Journal of Information Security and Applications, 72, Article 103398. https://doi.org/10.1016/j.jisa.2022.103398

Machine learning is key for automated detection of malicious network activity to ensure that computer networks and organizations are protected against cyber security attacks. Recently, there has been growing interest in the domain of adversarial mach... Read More about Defending against adversarial machine learning attacks using hierarchical learning: A case study on network traffic attack classification.

Interactive cyber-physical system hacking: Engaging students early using Scalextric (2022)
Presentation / Conference
White, J., Legg, P., & Mills, A. (2022, November). Interactive cyber-physical system hacking: Engaging students early using Scalextric. Paper presented at Colloquium on Information Systems Security Education, 2022, Online

Cyber Security as an education discipline covers a variety of topics that can be challenging and complex for students who are new to the subject domain. With this in mind, it is crucial that new students are motivated by understanding both the techni... Read More about Interactive cyber-physical system hacking: Engaging students early using Scalextric.

Teaching offensive and defensive cyber security in schools using a Raspberry Pi Cyber Range (2022)
Presentation / Conference
Legg, P., Mills, A., & Johnson, I. (2022, November). Teaching offensive and defensive cyber security in schools using a Raspberry Pi Cyber Range. Paper presented at Colloquium on Information Systems Security Education, Online

Computer Science as a subject is now appearing in more school curricula for GCSE and A level, with a growing demand for cyber security to be embedded within this teaching. Yet, teachers face challenges with limited time and resource for preparing pra... Read More about Teaching offensive and defensive cyber security in schools using a Raspberry Pi Cyber Range.

OGMA: Visualisation for software container security analysis and automated remediation (2022)
Conference Proceeding
Mills, A., White, J., & Legg, P. (2022). OGMA: Visualisation for software container security analysis and automated remediation. In 2022 IEEE International Conference on Cyber Security and Resilience (CSR) (76-81). https://doi.org/10.1109/CSR54599.2022.9850335

The use of software containerisation has rapidly increased in academia and industry which has lead to the production of several container security scanning tools for assessing the security posture and threat of a container image. The variability betw... Read More about OGMA: Visualisation for software container security analysis and automated remediation.

Functionality-preserving adversarial machine learning for robust classification in cybersecurity and intrusion detection domains: A survey (2022)
Journal Article
McCarthy, A., Ghadafi, E., Andriotis, P., & Legg, P. (2022). Functionality-preserving adversarial machine learning for robust classification in cybersecurity and intrusion detection domains: A survey. Journal of Cybersecurity and Privacy, 2(1), 154-190. https://doi.org/10.3390/jcp2010010

Machine learning has become widely adopted as a strategy for dealing with a variety of cybersecurity issues, ranging from insider threat detection to intrusion and malware detection. However, by their very nature, machine learning systems can introdu... Read More about Functionality-preserving adversarial machine learning for robust classification in cybersecurity and intrusion detection domains: A survey.

Investigating malware propagation and behaviour using system and network pixel-based visualisation (2021)
Journal Article
Williams, J., & Legg, P. (2022). Investigating malware propagation and behaviour using system and network pixel-based visualisation. SN Computer Science, 3(1), Article 53. https://doi.org/10.1007/s42979-021-00926-9

Malicious software, known as malware, is a perpetual game of cat and mouse between malicious software developers and security professionals. Recent years have seen many high profile cyber attacks, including the WannaCry and NotPetya ransomware attack... Read More about Investigating malware propagation and behaviour using system and network pixel-based visualisation.