All Outputs (8)

Investigating Machine Learning Attacks on Financial Time Series Models (2022)
Journal Article
Gallagher, M., Pitropakis, N., Chrysoulas, C., Papadopoulos, P., Mylonas, A., & Katsikas, S. (2022). Investigating Machine Learning Attacks on Financial Time Series Models. Computers and Security, 123, https://doi.org/10.1016/j.cose.2022.102933

Machine learning and Artificial Intelligence (AI) already support human decision-making and complement professional roles, and are expected in the future to be sufficiently trusted to make autonomous decisions. To trust AI systems with such tasks, a... Read More about Investigating Machine Learning Attacks on Financial Time Series Models.

Trusted Threat Intelligence Sharing in Practice and Performance Benchmarking through the Hyperledger Fabric Platform (2022)
Journal Article
Ali, H., Ahmad, J., Jaroucheh, Z., Papadopoulos, P., Pitropakis, N., Lo, O., …Buchanan, W. J. (2022). Trusted Threat Intelligence Sharing in Practice and Performance Benchmarking through the Hyperledger Fabric Platform. Entropy, 24(10), Article 1379. ht

Historically, threat information sharing has relied on manual modelling and centralised network systems, which can be inefficient, insecure, and prone to errors. Alternatively, private blockchains are now widely used to address these issues and impro... Read More about Trusted Threat Intelligence Sharing in Practice and Performance Benchmarking through the Hyperledger Fabric Platform.

Privacy-preserving systems around security, trust and identity (2022)
Thesis
Papadopoulos, P. Privacy-preserving systems around security, trust and identity. (Thesis). Edinburgh Napier University

Data has proved to be the most valuable asset in a modern world of rapidly advancing technologies. Companies are trying to maximise their profits by getting valuable insights from collected data about people’s trends and behaviour which often can be... Read More about Privacy-preserving systems around security, trust and identity.

GLASS: A Citizen-Centric Distributed Data-Sharing Model within an e-Governance Architecture (2022)
Journal Article
Lo, O., Buchanan, W., Sayeed, S., Papadopoulos, P., Pitropakis, N., & Chrysoulas, C. (2022). GLASS: A Citizen-Centric Distributed Data-Sharing Model within an e-Governance Architecture. Sensors, 22(6), Article 2291. https://doi.org/10.3390/s22062291

E-governance is a process that aims to enhance a government’s ability to simplify all the processes that may involve government, citizens, businesses, and so on. The rapid evolution of digital technologies has often created the necessity for the esta... Read More about GLASS: A Citizen-Centric Distributed Data-Sharing Model within an e-Governance Architecture.

Privacy-preserving and Trusted Threat Intelligence Sharing using Distributed Ledgers (2022)
Presentation / Conference Contribution
Ali, H., Papadopoulos, P., Ahmad, J., Pit, N., Jaroucheh, Z., & Buchanan, W. J. (2021, December). Privacy-preserving and Trusted Threat Intelligence Sharing using Distributed Ledgers. Presented at IEEE SINCONF: 14th International Conference on Security of

Threat information sharing is considered as one of the proactive defensive approaches for enhancing the overall security of trusted partners. Trusted partner organizations can provide access to past and current cybersecurity threats for reducing the... Read More about Privacy-preserving and Trusted Threat Intelligence Sharing using Distributed Ledgers.

Min-max Training: Adversarially Robust Learning Models for Network Intrusion Detection Systems (2022)
Presentation / Conference Contribution
Grierson, S., Thomson, C., Papadopoulos, P., & Buchanan, B. (2021, December). Min-max Training: Adversarially Robust Learning Models for Network Intrusion Detection Systems. Presented at 2021 14th International Conference on Security of Information and Ne

Intrusion detection systems are integral to the security of networked systems for detecting malicious or anomalous network traffic. As traditional approaches are becoming less effective, machine learning and deep learning-based intrusion detection sy... Read More about Min-max Training: Adversarially Robust Learning Models for Network Intrusion Detection Systems.

GLASS: Towards Secure and Decentralized eGovernance Services using IPFS (2022)
Presentation / Conference Contribution
Chrysoulas, C., Thomson, A., Pitropakis, N., Papadopoulos, P., Lo, O., Buchanan, W. J., Domalis, G., Karacapilidis, N., Tsakalidis, D., & Tsolis, D. (2021, October). GLASS: Towards Secure and Decentralized eGovernance Services using IPFS. Presented at 7th

The continuously advancing digitization has provided answers to the bureaucratic problems faced by eGovernance services. This innovation led them to an era of automation, broadened the attack surface and made them a popular target for cyber attacks.... Read More about GLASS: Towards Secure and Decentralized eGovernance Services using IPFS.

Ransomware: Analysing the Impact on Windows Active Directory Domain Services (2022)
Journal Article
McDonald, G., Papadopoulos, P., Pitropakis, N., Ahmad, J., & Buchanan, W. J. (2022). Ransomware: Analysing the Impact on Windows Active Directory Domain Services. Sensors, 22(3), Article 953. https://doi.org/10.3390/s22030953

Ransomware has become an increasingly popular type of malware across the past decade and continues to rise in popularity due to its high profitability. Organisations and enterprises have become prime targets for ransomware as they are more likely to... Read More about Ransomware: Analysing the Impact on Windows Active Directory Domain Services.