Skip to main content

Research Repository

Advanced Search

Evaluating data distribution strategies in federated learning: A trade-off analysis between privacy and performance for IoT security (2023)
Conference Proceeding
White, J., & Legg, P. (in press). Evaluating data distribution strategies in federated learning: A trade-off analysis between privacy and performance for IoT security.

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.

Digital twins in industry 4.0 cyber security (2023)
Conference Proceeding
Lo, C., Win, T. Y., Rezaeifar, Z., Khan, Z., & Legg, P. (in press). Digital twins in industry 4.0 cyber security. In IEEE Smart World Congress 2023 - IEEE SWC / UIC / ATC / ScalCom / Digital Twin / PCDS / Metaverse-2023

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.

Static analysis of security issues of the Python packages ecosystem (2023)
Journal Article
Gorine, A., & Spondon, F. (2023). Static analysis of security issues of the Python packages ecosystem. World Academy of Science, Engineering and Technology, 17(3), 33-40

Python is considered the most popular programming language and offers its own ecosystem for archiving and maintaining open-source software packages. This system is called the python package index (PyPI), the repository of this programming language. U... Read More about Static analysis of security issues of the Python packages ecosystem.

Formal verification of a hybrid machine learning-based fault prediction model in Internet of Things applications (2020)
Journal Article
Souri, A., Mohammed, A. S., Yousif Potrus, M., Malik, M. H., Safara, F., & Hosseinzadeh, M. (2020). Formal verification of a hybrid machine learning-based fault prediction model in Internet of Things applications. IEEE Access, 8, 23863-23874. https://doi.org/10.1109/ACCESS.2020.2967629

By increasing the complexity of the Internet of Things (IoT) applications, fault prediction become an important challenge in interactions between human, and smart devices. Fault prediction is one of the key factors to achieve better arranging the IoT... Read More about Formal verification of a hybrid machine learning-based fault prediction model in Internet of Things applications.

Performance analysis of IEEE 802.11a and IEEE 802.11g under Bursty traffic (2016)
Journal Article
Hussain Malik, M., Raza, S., Ilias Talukder, A. B. M., & Rafi, M. A. (2016). Performance analysis of IEEE 802.11a and IEEE 802.11g under Bursty traffic. Communications and Network, 14(10),

Technology from the end of last millennium, has been shifting with an unprecedented velocity scaling human anxiety down; communication technology, perhaps demonstrated the highest. Within the frontier of such profundities, reclines a key concern; Qua... Read More about Performance analysis of IEEE 802.11a and IEEE 802.11g under Bursty traffic.