Pavlos Papadopoulos
pavlos papadopoulos

Dr Pavlos Papadopoulos

Lecturer

Biography

Dr Pavlos Papadopoulos is a lecturer of cybersecurity at 麻豆社区, where he received his PhD in Privacy-Preserving Systems around Security, Trust and Identity in 2022, and an MSc in Advanced Security and Digital Forensics in 2019. He also holds a Bachelor's Degree in Digital Systems from the University of Piraeus, Greece. Pavlos is an Associate Fellow of the Higher Education Academy (AFHEA), and a member of the Blockpass Identity Lab (BIL). Pavlos has over 30 publications in international journals, conferences and books, and his research has been cited over 820 times. His research focuses on cybersecurity, distributed ledger technology, privacy-preserving machine learning, and related topics. In 2019, he and a team of PhD students from BIL won awards at the Diffusion Berlin hackathon for their work on "Identity and beyond with Hyperledger" and "Machine Learning in the Decentralized World". Additionally, Pavlos received the "Outstanding Young Person in Cyber" award at the Scottish Cyber Awards 2022. His expertise has led him to found TrueDeploy, a venture funded by Scottish Enterprise, Innovate UK, and the Royal Academy of Engineering for its innovative technology developed from Pavlos' PhD research which received the "Start Up of the Year" award at the Scottish Cyber Awards 2025. Pavlos has also been involved in teaching courses related to AWS and cloud concepts, operating systems, network security, penetration testing, incident response, and malware analysis.

Research Areas

News

Esteem

Fellowships and Awards

  • TrueDeploy nominated for the "Cyber Innovation Award" at Scottish Cyber Awards 2025
  • Winner (TrueDeploy) of the "Cyber Start-Up of the Year" award at Scottish Cyber Awards 2025
  • TrueDeploy nominated for the "RegTech Innovation" award at Scottish Financial Technology Awards 2024
  • Enterprise Fellowship (Royal Academy of Engineering)
  • TrueDeploy nominated for the "Best New Start-Up" award at Scottish Cyber Awards 2023
  • MDPI Computers Journal Cover: 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), 32.

 

Date


25 results

Asymmetric Private Set Intersection with Applications to Contact Tracing and Private Vertical Federated Machine Learning

Presentation / Conference
Angelou, N., Benaissa, A., Cebere, B., Clark, W., Hall, A. J., Hoeh, M. A., 鈥itcombe, T. (2020, December)
Asymmetric Private Set Intersection with Applications to Contact Tracing and Private Vertical Federated Machine Learning. Poster presented at NeurIPS 2020 Workshop on Privacy Preserving Machine Learning (PPML 2020), Online
We present a multi-language, cross-platform, open-source library for asymmetric private set intersection (PSI) and PSI-Cardinality (PSI-C). Our protocol combines traditional D...

Review and Critical Analysis of Privacy-preserving Infection Tracking and Contact Tracing

Journal Article
Buchanan, W. J., Imran, M. A., Ur-Rehman, M., Zhang, L., Abbasi, Q. H., Chrysoulas, C., 鈥apadopoulos, P. (2020)
Review and Critical Analysis of Privacy-preserving Infection Tracking and Contact Tracing. Frontiers in Communications and Networks, https://doi.org/10.3389/frcmn.2020.583376
The outbreak of viruses have necessitated contact tracing and infection tracking methods. Despite various efforts, there is currently no standard scheme for the tracing and tr...

A Privacy-Preserving Healthcare Framework Using Hyperledger Fabric

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), 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 ofte...

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 ...

Privacy-Preserving Passive DNS

Journal Article
Papadopoulos, P., Pitropakis, N., Buchanan, W. J., Lo, O., & Katsikas, S. (2020)
Privacy-Preserving Passive DNS. Computers, 9(3), 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...

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