Outputs (8)

Decentralised Privacy: A Distributed Ledger Approach (2021)
Book Chapter
Papadopoulos, P., Pitropakis, N., & Buchanan, W. J. (2021). Decentralised Privacy: A Distributed Ledger Approach. In C. Mustansar Hussain, & P. Di Sia (Eds.), Handbook of Smart Materials, Technologies, and Devices (1-26). Cham: Springer. https://doi.org/1

Our world due to the technological progress became fast-paced and is constantly evolving, thus changing every single day. Consequently, the most valuable asset on earth is not gold or oil anymore but data. Big data companies try to take advantage of... Read More about Decentralised Privacy: A Distributed Ledger Approach.

Browsers’ Private Mode: Is It What We Were Promised? (2021)
Journal Article
Hughes, K., Papadopoulos, P., Pitropakis, N., Smales, A., Ahmad, J., & Buchanan, W. J. (2021). Browsers’ Private Mode: Is It What We Were Promised?. Computers, 10(12), Article 165. https://doi.org/10.3390/computers10120165

Web browsers are one of the most used applications on every computational device in our days. Hence, they play a pivotal role in any forensic investigation and help determine if nefarious or suspicious activity has occurred on that device. Our study... Read More about Browsers’ Private Mode: Is It What We Were Promised?.

Evaluating Tooling and Methodology when Analysing Bitcoin Mixing Services After Forensic Seizure (2021)
Presentation / Conference Contribution
Young, E. H., Chrysoulas, C., Pitropakis, N., Papadopoulos, P., & Buchanan, W. J. (2021, October). Evaluating Tooling and Methodology when Analysing Bitcoin Mixing Services After Forensic Seizure. Paper presented at International Conference on Data Analyt

Little or no research has been directed to analysis and researching forensic analysis of the Bitcoin mixing or 'tumbling' service themselves. This work is intended to examine effective tooling and methodology for recovering forensic artifacts from tw... Read More about Evaluating Tooling and Methodology when Analysing Bitcoin Mixing Services After Forensic Seizure.

PyDentity: A playground for education and experimentation with the hyperledger verifiable information exchange platform (2021)
Journal Article
Abramson, W., Papadopoulos, P., Pitropakis, N., & Buchanan, W. J. (2021). PyDentity: A playground for education and experimentation with the hyperledger verifiable information exchange platform. Software Impacts, 9, Article 100101. https://doi.org/10.1016

PyDentity lowers the entry barrier for parties interested in experimenting with the Hyperledger’s verifiable information exchange platform. It enables educators, developers and researchers to configure and initialise a set of actors easily as associa... Read More about PyDentity: A playground for education and experimentation with the hyperledger verifiable information exchange platform.

PyVertical: A Vertical Federated Learning Framework for Multi-headed SplitNN (2021)
Presentation / Conference Contribution
Romanini, D., Hall, A. J., Papadopoulos, P., Titcombe, T., Ismail, A., Cebere, T., …Hoeh, M. A. (2021, May). PyVertical: A Vertical Federated Learning Framework for Multi-headed SplitNN. Poster presented at ICLR 2021 Workshop on Distributed and Private

We introduce PyVertical, a framework supporting vertical federated learning using split neural networks. The proposed framework allows a data scientist to train neural networks on data features vertically partitioned across multiple owners while keep... Read More about PyVertical: A Vertical Federated Learning Framework for Multi-headed SplitNN.

Practical defences against model inversion attacks for split neural networks (2021)
Presentation / Conference Contribution
Titcombe, T., Hall, A. J., Papadopoulos, P., & Romanini, D. (2021, May). Practical defences against model inversion attacks for split neural networks. Paper presented at ICLR 2021 Workshop on Distributed and Private Machine Learning (DPML 2021), Online

We describe a threat model under which a split network-based federated learning system is susceptible to a model inversion attack by a malicious computational server. We demonstrate that the attack can be successfully performed with limited knowledge... Read More about Practical defences against model inversion attacks for split neural networks.

Launching Adversarial Attacks against Network Intrusion Detection Systems for IoT (2021)
Journal Article
Papadopoulos, P., Thornewill Von Essen, O., Pitropakis, N., Chrysoulas, C., Mylonas, A., & Buchanan, W. J. (2021). Launching Adversarial Attacks against Network Intrusion Detection Systems for IoT. Journal of Cybersecurity and Privacy, 1(2), 252-273. http

As the internet continues to be populated with new devices and emerging technologies, the attack surface grows exponentially. Technology is shifting towards a profit-driven Internet of Things market where security is an afterthought. Traditional defe... Read More about Launching Adversarial Attacks against Network Intrusion Detection Systems for IoT.

Privacy and Trust Redefined in Federated Machine Learning (2021)
Journal Article
Papadopoulos, P., Abramson, W., Hall, A. J., Pitropakis, N., & Buchanan, W. J. (2021). Privacy and Trust Redefined in Federated Machine Learning. Machine Learning and Knowledge Extraction, 3(2), 333-356. https://doi.org/10.3390/make3020017

A common privacy issue in traditional machine learning is that data needs to be disclosed for the training procedures. In situations with highly sensitive data such as healthcare records, accessing this information is challenging and often prohibited... Read More about Privacy and Trust Redefined in Federated Machine Learning.