Distributed Reconstruction of Sensor Cyber-Attacks in Cyber-Physical Networks

Critical infrastructures, such as power and transportation, are frequently modeled as interconnected Cyber-Physical Systems (CPS). This interconnectivity makes CPS vulnerable to cyber-attacks, threatening system stability and operational continuity. Notably, many of these malicious attacks involve manipulating sensor measurements. In this context, accurately reconstructing the attack signal is crucial for recovering true measurements, distinguishing cyber-attacks from faults, and enabling effective countermeasures. This work presents a distributed scheme that leverages sliding mode observers to reconstruct attack signals targeting sensors in heterogeneous linear cyber-physical networks. The proposed approach achieves attack reconstruction with suitable bounds on the reconstruction error that depend on the system disturbance characteristics. Additionally, we present an isolation mechanism that utilizes the developed reconstruction scheme and analytically show that it accurately determines the attacked nodes. The applicability of the proposed approach is demonstrated through numerical simulations on a six-subsystem interconnected system, which validate our analytic results.