Secure estimation and control for cyber-physical systems under adversarial attacks
This addresses security vulnerabilities in critical infrastructure control systems, which is an incremental advancement in cyber-physical system security.
The paper tackles the problem of secure estimation and control for linear cyber-physical systems under adversarial attacks on sensors or actuators, proposing an efficient algorithm for state estimation and showing that resilient output-feedback controllers can be designed based on resilient state estimators.
The vast majority of today's critical infrastructure is supported by numerous feedback control loops and an attack on these control loops can have disastrous consequences. This is a major concern since modern control systems are becoming large and decentralized and thus more vulnerable to attacks. This paper is concerned with the estimation and control of linear systems when some of the sensors or actuators are corrupted by an attacker. In the first part we look at the estimation problem where we characterize the resilience of a system to attacks and study the possibility of increasing its resilience by a change of parameters. We then propose an efficient algorithm to estimate the state despite the attacks and we characterize its performance. Our approach is inspired from the areas of error-correction over the reals and compressed sensing. In the second part we consider the problem of designing output-feedback controllers that stabilize the system despite attacks. We show that a principle of separation between estimation and control holds and that the design of resilient output feedback controllers can be reduced to the design of resilient state estimators.