Information Theory Approaches for Cyberattack Detection and Fault Identification in Power Systems

Power systems, the backbone of modern society, rely heavily on digital control and communication technologies, rendering them vulnerable to sophisticated cyberattacks such as False Data Injection (FDI) and intrusion attempts. Traditional methods, rooted in signature-based detection and rule-based systems, need help to keep pace with the dynamic threat landscape. In response to these challenges, this paper proposes an innovative framework for cyberattack detection and fault localization inspired by the principles of information theory. By harnessing concepts such as entropy, mutual information, and data compression, this framework doesn’t just detect anomalies; it quantifies information and dissects uncertainty. This results in a more timely and precise identification of subtle anomalies and threats that might otherwise slip through the cracks of traditional methods. This research contributes to enhancing the resilience of power systems, ensuring a steady supply of electricity, and fortifying the security of the critical infrastructure that supports our way of life.