338 citations · 457 across the 10 of their papers we have counts for
11 papers
Federated Learning for Tabular Data: Exploring Potential Risk to Privacy
Han Wu, Zilong Zhao, Lydia Y. Chen +1
Federated Learning (FL) has emerged as a potentially powerful privacy-preserving machine learning methodology, since it avoids exchanging data between participants, but instead exc…
Identifying and Supporting Financially Vulnerable Consumers in a Privacy-Preserving Manner: A Use Case Using Decentralised Identifiers and Verifiable Credentials
Tasos Spiliotopoulos, Dave Horsfall, Magdalene Ng +3
Vulnerable individuals have a limited ability to make reasonable financial decisions and choices and, thus, the level of care that is appropriate to be provided to them by financia…
Stochastic Simulation Techniques for Inference and Sensitivity Analysis of Bayesian Attack Graphs
Isaac Matthews, Sadegh Soudjani, Aad van Moorsel
A vulnerability scan combined with information about a computer network can be used to create an attack graph, a model of how the elements of a network could be used in an attack t…
Investigation of 3-D Secure's Model for Fraud Detection
Mohammed Aamir Ali, Thomas Groß, Aad van Moorsel
Background. 3-D Secure 2.0 (3DS 2.0) is an identity federation protocol authenticating the payment initiator for credit card transactions on the Web. Aim. We aim to quantify the im…
Simulating the Effects of Social Presence on Trust, Privacy Concerns & Usage Intentions in Automated Bots for Finance
Magdalene Ng, Kovila P. L. Coopamootoo, Ehsan Toreini +3
FinBots are chatbots built on automated decision technology, aimed to facilitate accessible banking and to support customers in making financial decisions. Chatbots are increasing…
Cyclic Bayesian Attack Graphs: A Systematic Computational Approach
Isaac Matthews, John Mace, Sadegh Soudjani +1
Attack graphs are commonly used to analyse the security of medium-sized to large networks. Based on a scan of the network and likelihood information of vulnerabilities, attack grap…
Data-Driven Model-Based Analysis of the Ethereum Verifier's Dilemma
Maher Alharby, Roben Castagna Lunardi, Amjad Aldweesh +1
In proof-of-work based blockchains such as Ethereum, verification of blocks is an integral part of establishing consensus across nodes. However, in Ethereum, miners do not receive…
BlockSim: An Extensible Simulation Tool for Blockchain Systems
Maher Alharby, Aad van Moorsel
Both in the design and deployment of blockchain solutions many performance-impacting configuration choices need to be made. We introduce BlockSim, a framework and software tool to…
The relationship between trust in AI and trustworthy machine learning technologies
Ehsan Toreini, Mhairi Aitken, Kovila Coopamootoo +3
To build AI-based systems that users and the public can justifiably trust one needs to understand how machine learning technologies impact trust put in these services. To guide tec…
Blockchain-based Smart Contracts: A Systematic Mapping Study
Maher Alharby, Aad van Moorsel
An appealing feature of blockchain technology is smart contracts. A smart contract is executable code that runs on top of the blockchain to facilitate, execute and enforce an agree…
Betrayal, Distrust, and Rationality: Smart Counter-Collusion Contracts for Verifiable Cloud Computing
Changyu Dong, Yilei Wang, Amjad Aldweesh +2
Cloud computing has become an irreversible trend. Together comes the pressing need for verifiability, to assure the client the correctness of computation outsourced to the cloud. E…