Secure estimation and control for cyber-physical systems under adversarial attacks

TL;DR

This paper addresses the challenge of estimating and controlling linear systems in cyber-physical systems under adversarial sensor and actuator attacks, proposing new algorithms and design principles for resilience.

Contribution

It introduces an efficient state estimation algorithm resilient to attacks and establishes a separation principle for designing resilient output-feedback controllers.

Findings

Proposed an attack-resilient state estimation algorithm inspired by error correction and compressed sensing.

Characterized system resilience and how parameter changes can improve it.

Demonstrated that resilient control design reduces to resilient state estimation.

Abstract

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.