Stealthy Sensor Attack Detection and Real-Time Performance Recovery for Resilient CPS

Cyber-physical attacks exploit intrinsic natures of physical systems and can severely damage cyber-physical systems (CPSs) without being detected by the conventional anomaly detector. In this paper, based on software-defined networking, we propose a holistic resilient CPS framework that can detect, isolate, and recover from cyber-physical attacks in real-time. To show the effectiveness of the proposed framework, we focus on the pole-dynamics attack (PDA), a newly reported stealthy sensor attack that can make the physical system unstable. We develop an efficient detection algorithm for PDA and embed it into the proposed framework. By implementing a testbed, we validate that the proposed framework guarantees resilience of CPS against the PDA.