Скачать или смотреть Intrusion Detection and Mitigation tools for Power Grid - CARS'22 Virtual Session

Cyber-physical security (CPS) research for the smart grid is currently one of the nation’s top research and development (R&D) priorities. In the past 10 years, there has been a remarkable enhancement in developing wide-area applications in the energy management system (EMS) to provide an adequate situational awareness to control center operators. Meanwhile, there has been a growing trend of cyber threats, targeting critical Industrial control system (ICS) infrastructure around the world. The evolving cyber threats (e.g., Stuxnet, Ukraine power grid attacks, and Colonial Pipeline attack) due to rapid digitalization, unencrypted communication, and numerous data-sharing devices underscore the importance and urgency to develop an attack-resilient grid through innovative cybersecurity solutions. This presentation presents a data-driven approach to develop intrusion detection and mitigation tools against cybersecurity threats in the smart grid. In particular, the proposed anomaly detection methodology applies state-of-the-art machine learning algorithms to detect anomalies and physical disturbances that are integrated with rules-based mitigation measures to restore the grid to the normal operating state. Finally, we will discuss the NREL’s Cyber Range platform for experimental testing and attack-detection evaluation using several performance measures.