activity
20192025
most citedA Privacy-Preserving Healthcare Framework Using Hyperledger Fabric

141 citations · 404 across the 22 of their papers we have counts for

collaborators
Showing 2021Show all

6 papers · 1 filter

cs.CR2021★ 1 cited

Privacy-preserving and Trusted Threat Intelligence Sharing using Distributed Ledgers

Hisham Ali, Pavlos Papadopoulos, Jawad Ahmad +3

Threat information sharing is considered as one of the proactive defensive approaches for enhancing the overall security of trusted partners. Trusted partner organizations can prov…

cs.CR2021

PAN-DOMAIN: Privacy-preserving Sharing and Auditing of Infection Identifier Matching

William Abramson, William J. Buchanan, Sarwar Sayeed +2

The spread of COVID-19 has highlighted the need for a robust contact tracing infrastructure that enables infected individuals to have their contacts traced, and followed up with a…

cs.CR2021

Evaluating Tooling and Methodology when Analysing Bitcoin Mixing Services After Forensic Seizure

Edward Henry Young, Christos Chrysoulas, Nikolaos Pitropakis +2

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 effec…

cs.CR2021

GLASS: Towards Secure and Decentralized eGovernance Services using IPFS

Christos Chrysoulas, Amanda Thomson, Nikolaos Pitropakis +7

The continuously advancing digitization has provided answers to the bureaucratic problems faced by eGovernance services. This innovation led them to an era of automation it has bro…

cs.LG2021★ 78 cited

Launching Adversarial Attacks against Network Intrusion Detection Systems for IoT

Pavlos Papadopoulos, Oliver Thornewill von Essen, Nikolaos Pitropakis +3

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 Interne…

cs.CR2021★ 44 cited

Privacy and Trust Redefined in Federated Machine Learning

Pavlos Papadopoulos, Will Abramson, Adam J. Hall +2

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 r…