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RX-ADS: Interpretable Anomaly Detection using Adversarial ML for Electric Vehicle CAN data
Recent year has brought considerable advancements in Electric Vehicles (EVs) and associated infrastructures/communications.
Multi-Agent Learning for Resilient Distributed Control Systems
In this book chapter, we present a multi-agent system (MAS) framework for distributed large-scale control systems and discuss the role of MAS learning in resiliency.
Self-Supervised and Interpretable Anomaly Detection using Network Transformers
Monitoring traffic in computer networks is one of the core approaches for defending critical infrastructure against cyber attacks.
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