5 papers
ExMo: Explainable AI Model using Inverse Frequency Decision Rules
Pradip Mainali, Ismini Psychoula, Fabien A. P. Petitcolas
In this paper, we present a novel method to compute decision rules to build a more accurate interpretable machine learning model, denoted as ExMo. The ExMo interpretable machine le…
Explainable Machine Learning for Fraud Detection
Ismini Psychoula, Andreas Gutmann, Pradip Mainali +3
The application of machine learning to support the processing of large datasets holds promise in many industries, including financial services. However, practical issues for the fu…
PINFER: Privacy-Preserving Inference for Machine Learning
Marc Joye, Fabien A. P. Petitcolas
The foreseen growing role of outsourced machine learning services is raising concerns about the privacy of user data. Several technical solutions are being proposed to address the…
Privacy-Enhancing Context Authentication from Location-Sensitive Data
Pradip Mainali, Carlton Shepherd, Fabien A. P. Petitcolas
This paper proposes a new privacy-enhancing, context-aware user authentication system, ConSec, which uses a transformation of general location-sensitive data, such as GPS location,…
A First Look at Identity Management Schemes on the Blockchain
Paul Dunphy, Fabien A. P. Petitcolas
The emergence of distributed ledger technology (DLT) based upon a blockchain data structure, has given rise to new approaches to identity management that aim to upend dominant appr…