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cs.LG2024
Machine Theory of Mind for Autonomous Cyber-Defence
Luke Swaby, Matthew Stewart, Daniel Harrold +2
Intelligent autonomous agents hold much potential for the domain of cyber-security. However, due to many state-of-the-art approaches relying on uninterpretable black-box models, th…
cs.LG2024
Enhanced Federated Anomaly Detection Through Autoencoders Using Summary Statistics-Based Thresholding
Sofiane Laridi, Gregory Palmer, Kam-Ming Mark Tam
In Federated Learning (FL), anomaly detection (AD) is a challenging task due to the decentralized nature of data and the presence of non-IID data distributions. This study introduc…