Cyber-Physical Systems Security & Anomaly Detection

As industrial and automotive systems grow more connected, ISACLAB researches how to detect and mitigate cyberattacks, sensor faults, and anomalies before they compromise safety. We design secure control and sensor-fusion strategies for industrial gas turbines, and deep-learning-based intrusion detection and fault-tolerant cruise control for connected and autonomous vehicles, addressing actuator lag, communication delay, and adversarial sensor manipulation. This research has appeared in IEEE Transactions on Industrial Cyber-Physical Systems and IEEE Sensors Journal, often with international collaborators.