Control Barrier Function-Based Attack Recovery With Provable Guarantees

This paper investigates security guarantees for cyber-physical systems (CPS) against actuator attacks. We in troduce a new attack detection mechanism based on zeroing control barrier function (ZCBF) conditions. We propose an adaptive recovery mechanism that responds based on the system's proximity to safety violations. Our attack-detection mechanism has been proven to be sound, meaning it consistently detects adversarial attacks without any false negatives. Additionally, we propose a novel hybrid control law that addresses delays in attack detection and prevents Zeno behavior. We also propose a sampling-based method to verify whether a set is a viability domain for CPS. Finally, we employ a Quadratic Programming (QP) approach for synthesizing control laws for the hybrid control policy, utilizing the viability domain to ensure safety in the presence of adversarial attacks on system actuators. The efficacy of the proposed method is demonstrated in a simulation case study involving a quadrotor system.