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...
A Distributed Trust Framework for Privacy-Preserving Machine Learning
Conference Proceeding
Abramson, W., Hall, A. J., Papadopoulos, P., Pitropakis, N., & Buchanan, W. J. (2020)
A Distributed Trust Framework for Privacy-Preserving Machine Learning. In Trust, Privacy and Security in Digital Business. , (205-220). https://doi.org/10.1007/978-3-030-58986-8_14
When training a machine learning model, it is standard procedure for the researcher to have full knowledge of both the data and model. However, this engenders a lack of trust ...
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...
Phishing URL Detection Through Top-Level Domain Analysis: A Descriptive Approach
Conference Proceeding
Christou, O., Pitropakis, N., Papadopoulos, P., Mckeown, S., & Buchanan, W. J. (2020)
Phishing URL Detection Through Top-Level Domain Analysis: A Descriptive Approach. In Proceedings of the 6th International Conference on Information Systems Security and Privacy. , (289-298). https://doi.org/10.5220/0008902202890298
Phishing is considered to be one of the most prevalent cyber-attacks because of its immense flexibility and alarmingly high success rate. Even with adequate training and high ...
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...