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Dr Pavlos Papadopoulos' Outputs (28)

A Privacy-Preserving Healthcare Framework Using Hyperledger Fabric (2020)
Journal Article
Stamatellis, C., Papadopoulos, P., Pitropakis, N., Katsikas, S., & Buchanan, W. J. (2020). A Privacy-Preserving Healthcare Framework Using Hyperledger Fabric. Sensors, 20(22), Article 6587. https://doi.org/10.3390/s20226587

Electronic health record (EHR) management systems require the adoption of effective technologies when health information is being exchanged. Current management approaches often face risks that may expose medical record storage solutions to common sec... Read More about A Privacy-Preserving Healthcare Framework Using Hyperledger Fabric.

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.

Privacy-Preserving Passive DNS (2020)
Journal Article
Papadopoulos, P., Pitropakis, N., Buchanan, W. J., Lo, O., & Katsikas, S. (2020). Privacy-Preserving Passive DNS. Computers, 9(3), Article 64. https://doi.org/10.3390/computers9030064

The Domain Name System (DNS) was created to resolve the IP addresses of web servers to easily remembered names. When it was initially created, security was not a major concern; nowadays, this lack of inherent security and trust has exposed the global... Read More about Privacy-Preserving Passive DNS.

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.

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). Springer. https://doi.org/10.1007/978-3-030-58675-1_58-1

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.

Towards a Secure Manufacturing Framework for Single Malt Whisky in Industry 4.0 (2025)
Presentation / Conference Contribution
Connell, J., Kasimatis, D., Papadopoulos, P., Buchanan, W. J., Sarigiannidis, P., & Pitropakis, N. (2024, June). Towards a Secure Manufacturing Framework for Single Malt Whisky in Industry 4.0. Presented at International Conference on Cybersecurity, Situational Awareness and Social Media (Cyber Science 2024), Edinburgh, UK

Recent instances have brought to light the inherent vulnerability of the manufacturing sector to cyber security threats, particularly within the food and beverage industries. With the rapid adoption of Industry 4.0, supply chains are exposed to an ex... Read More about Towards a Secure Manufacturing Framework for Single Malt Whisky in Industry 4.0.

DID:RING: Ring Signatures Using Decentralised Identifiers For Privacy-Aware Identity Proof (2024)
Presentation / Conference Contribution
Kasimatis, D., Grierson, S., Buchanan, W. J., Eckl, C., Papadopoulos, P., Pitropakis, N., Chrysoulas, C., Thomson, C., & Ghaleb, B. (2024, September). DID:RING: Ring Signatures Using Decentralised Identifiers For Privacy-Aware Identity Proof. Presented at 2024 IEEE International Conference on Cyber Security and Resilience (CSR), London, UK

Decentralised identifiers have become a standardised element of digital identity architecture, with supra-national organisations such as the European Union adopting them as a key component for a unified European digital identity ledger. This paper de... Read More about DID:RING: Ring Signatures Using Decentralised Identifiers For Privacy-Aware Identity Proof.

Transforming EU Governance: The Digital Integration Through EBSI and GLASS (2024)
Presentation / Conference Contribution
Kasimatis, D., Buchanan, W. J., Abubakar, M., Lo, O., Chrysoulas, C., Pitropakis, N., Papadopoulos, P., Sayeed, S., & Sel, M. (2024, June). Transforming EU Governance: The Digital Integration Through EBSI and GLASS. Presented at 39th IFIP International Conference, Edinburgh, UK

Traditionally, government systems managed citizen identities through disconnected data systems, using simple identifiers and paper-based processes, limiting digital trust and requiring citizens to request identity verification documents. The digital... Read More about Transforming EU Governance: The Digital Integration Through EBSI and GLASS.

Explainable AI-Based DDOS Attack Identification Method for IoT Networks (2023)
Journal Article
Kalutharage, C. S., Liu, X., Chrysoulas, C., Pitropakis, N., & Papadopoulos, P. (2023). Explainable AI-Based DDOS Attack Identification Method for IoT Networks. Computers, 12(2), Article 32. https://doi.org/10.3390/computers12020032

The modern digitized world is mainly dependent on online services. The availability of online systems continues to be seriously challenged by distributed denial of service (DDoS) attacks. The challenge in mitigating attacks is not limited to identify... Read More about Explainable AI-Based DDOS Attack Identification Method for IoT Networks.

Towards The Creation Of The Future Fish Farm (2023)
Journal Article
Papadopoulos, P., Buchanan, W. J., Sayeed, S., & Pitropakis, N. (2023). Towards The Creation Of The Future Fish Farm. Journal of Surveillance, Security and Safety, 4, 1-3. https://doi.org/10.20517/jsss.2022.16

Aim: A fish farm is an area where fish raise and bred for food. Fish farm environments support the care and management of seafood within a controlled environment. Over the past few decades, there has been a remarkable increase in the calorie intake o... Read More about Towards The Creation Of The Future Fish Farm.

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., Abramson, W., & Buchanan, W. J. (2022). Trusted Threat Intelligence Sharing in Practice and Performance Benchmarking through the Hyperledger Fabric Platform. Entropy, 24(10), Article 1379. https://doi.org/10.3390/e24101379

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 Information and Networks, Edinburgh

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 Networks (SIN), Edinburgh, United Kingdom

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 Workshop On The Security Of Industrial Control Systems & Of Cyber-Physical Systems (CyberICPS 2021). In Conjunction With ESORICS 2021, Darmstadt, Germany

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.

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 Analytics for Business and Industry (ICDABI) 2021 - (DATA'21), Online

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.