Can Federated Models Be Rectified Through Learning Negative Gradients?
Conference Proceeding
Tahir, A., Tan, Z., & Babaagba, K. O. (2024)
Can Federated Models Be Rectified Through Learning Negative Gradients?. In Big Data Technologies and Applications (18-32). https://doi.org/10.1007/978-3-031-52265-9_2
Federated Learning (FL) is a method to train machine learning (ML) models in a decentralised manner, while preserving the privacy of data from multiple clients. However, FL is...
PAN-DOMAIN: Privacy-preserving Sharing and Auditing of Infection Identifier Matching
Conference Proceeding
Abramson, W., Buchanan, W. J., Sayeed, S., Pitropakis, N., & Lo, O. (2022)
PAN-DOMAIN: Privacy-preserving Sharing and Auditing of Infection Identifier Matching. In 14th International Conference on Security of Information and Networks. https://doi.org/10.1109/SIN54109.2021.9699138
The spread of COVID-19 has highlighted the need for a robust contact tracing infrastructure that enables infected individuals to have their contacts traced, and followed up wi...
Privacy-preserving and Trusted Threat Intelligence Sharing using Distributed Ledgers
Conference Proceeding
Ali, H., Papadopoulos, P., Ahmad, J., Pit, N., Jaroucheh, Z., & Buchanan, W. J. (2022)
Privacy-preserving and Trusted Threat Intelligence Sharing using Distributed Ledgers. In IEEE SINCONF: 14th International Conference on Security of Information and Networks. https://doi.org/10.1109/SIN54109.2021.9699366
Threat information sharing is considered as one of the proactive defensive approaches for enhancing the overall security of trusted partners. Trusted partner organizations can...
GLASS: Towards Secure and Decentralized eGovernance Services using IPFS
Conference Proceeding
Chrysoulas, C., Thomson, A., Pitropakis, N., Papadopoulos, P., Lo, O., Buchanan, W. J., …Tsolis, D. (2022)
GLASS: Towards Secure and Decentralized eGovernance Services using IPFS. In Computer Security. ESORICS 2021 International Workshops. https://doi.org/10.1007/978-3-030-95484-0_3
The continuously advancing digitization has provided answers to the bureaucratic problems faced by eGovernance services. This innovation led them to an era of automation, broa...
Blockchain-Based Authentication and Registration Mechanism for SIP-Based VoIP Systems
Conference Proceeding
Abubakar, M., Jaroucheh, Z., Al Dubai, A., & Buchanan, W. (2021)
Blockchain-Based Authentication and Registration Mechanism for SIP-Based VoIP Systems. In 2021 5th Cyber Security in Networking Conference (CSNet). https://doi.org/10.1109/csnet52717.2021.9614646
The Session Initiation Protocol (SIP) is the principal signalling protocol in Voice over IP (VoIP) systems, responsible for initialising, terminating, and maintaining sessions...
A Privacy-Preserving Platform for Recording COVID-19 Vaccine Passports
Conference Proceeding
Barati, M., Buchanan, W. J., Lo, O., & Rana, O. (2022)
A Privacy-Preserving Platform for Recording COVID-19 Vaccine Passports. In UCC '21: Proceedings of the 14th IEEE/ACM International Conference on Utility and Cloud Computing Companion. https://doi.org/10.1145/3492323.3495626
Digital vaccination passports are being proposed by various governments internationally. Trust, scalability and security are all key challenges in implementing an online vacci...
A Decentralised Authentication and Access Control Mechanism for Medical Wearable Sensors Data
Conference Proceeding
Abubakar, M., Jaroucheh, Z., Al Dubai, A., & Buchanan, W. J. (2021)
A Decentralised Authentication and Access Control Mechanism for Medical Wearable Sensors Data. In 2021 IEEE International Conference on Omni-Layer Intelligent Systems (COINS). https://doi.org/10.1109/coins51742.2021.9524172
Recent years have seen an increase in medical big data, which can be attributed to a paradigm shift experienced in medical data sharing induced by the growth of medical techno...
Min-max Training: Adversarially Robust Learning Models for Network Intrusion Detection Systems
Conference Proceeding
Grierson, S., Thomson, C., Papadopoulos, P., & Buchanan, B. (2022)
Min-max Training: Adversarially Robust Learning Models for Network Intrusion Detection Systems. In 2021 14th International Conference on Security of Information and Networks (SIN). https://doi.org/10.1109/sin54109.2021.9699157
Intrusion detection systems are integral to the security of networked systems for detecting malicious or anomalous network traffic. As traditional approaches are becoming less...