ANALYSE -- Learning to Attack Cyber-Physical Energy Systems With Intelligent Agents. (arXiv:2305.09476v1 [cs.CR])

The ongoing penetration of energy systems with information and communications
technology (ICT) and the introduction of new markets increase the potential for
malicious or profit-driven attacks that endanger system stability. To ensure
security-of-supply, it is necessary to analyze such attacks and their
underlying vulnerabilities, to develop countermeasures and improve system
design. We propose ANALYSE, a machine-learning-based software suite to let
learning agents autonomously find attacks in cyber-physical energy systems,
consisting of the power system, ICT, and energy markets. ANALYSE is …

attack attacks communications countermeasures cyber energy information introduction malicious markets penetration physical profit security supply system systems technology vulnerabilities