All Outputs (4)

Evaluating data distribution strategies in federated learning: A trade-off analysis between privacy and performance for IoT security (2023)
Presentation / Conference Contribution
White, J., & Legg, P. (2023, December). Evaluating data distribution strategies in federated learning: A trade-off analysis between privacy and performance for IoT security. Presented at 9th International Conference on Cyber Security and Privacy, Cardiff, UK

Federated learning is an effective approach for training a global machine learning model. It uses locally acquired data without having to share local data with the centralised server. This method provides a machine learning model beneficial for all p... Read More about Evaluating data distribution strategies in federated learning: A trade-off analysis between privacy and performance for IoT security.

Longitudinal risk-based security assessment of docker software container images (2023)
Journal Article
Mills, A., White, J., & Legg, P. (2023). Longitudinal risk-based security assessment of docker software container images. Computers and Security, 135, Article 103478. https://doi.org/10.1016/j.cose.2023.103478

As the use of software containerisation has increased, so too has the need for security research on their usage, with various surveys and studies conducted to assess the overall security posture of software container images. To date, there has been v... Read More about Longitudinal risk-based security assessment of docker software container images.

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.

Interactive cyber-physical system hacking: Engaging students early using scalextric (2023)
Presentation / Conference Contribution
White, J., Legg, P., & Mills, A. Interactive cyber-physical system hacking: Engaging students early using scalextric

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.