UC Berkeley

We address the problem of detecting and mitigating the effect of malicious attacks on the sensors of a linear dynamical system. We develop a novel, efficient algorithm that uses a Satisfiability Modulo Theory approach to isolate the compromised sensors and estimate the system state despite the presence of the attack, thus harnessing the intrinsic combinatorial complexity of the problem. Simulation results show that our algorithm compares favorably with alternative techniques, with respect to both runtime and estimation error.