In this paper, we design a novel control architecture that prevents the existence of intelligent and undetectable cyber-attacks against networked control systems (e.g., replay and covert attacks). In particular, first, we propose to encode the sensor outputs into a randomly changing lowerdimensional space obtained by means of principal component analysis. Such a transformation ensures optimal information reconstruction on the controller’s side, and it prevents the attacker from accessing the original sensor measurements, nullifying the possibility of perfect stealthy attacks. Then, on the controller’s side, we design a passive Gaussian anomaly detector that leverages the output of an unknown input observer ad-hoc designed to estimate the system’s states and unknown inputs simultaneously. It is formally shown that the proposed detection strategy is able to discover the presence of replay and covert attacks. Simulation results obtained considering a quadruple water tank system confirm the capability of the developed architecture.

M. Attar, W. Lucia,  "An Active Detection Strategy Based on Dimensionality Reduction for False Data Injection Attacks in Cyber-Physical Systems", IEEE Transactions on Control of Network Systems (CONES), DOI 10.1109/TCNS.2023.3244103, 2023