On the detection of the presence of malicious components in cyber-physical systems in the almost sure sense

TL;DR

This paper addresses the fundamental problem of almost sure detection of malicious components in cyber-physical systems, introducing new conditions and methods for identifying malicious actuators under stochastic models.

Contribution

It establishes necessary and sufficient conditions for malicious actuator detection in CPSs modeled as Markov decision processes and stochastic linear systems.

Findings

Necessary and sufficient conditions for detection in MDP-modeled CPSs.

Conditions for detectability with randomized control policies.

Analysis of perturbation methods for malicious actuator detection.

Abstract

This article studies a fundamental problem of security of cyber-physical systems (CPSs): that of detecting, almost surely, the presence of malicious components in the CPS. We assume that some of the actuators may be malicious while all sensors are honest. We introduce a novel idea of separability of state trajectories generated by CPSs in two situations: those under the nominal no-attack situation and those under the influence of an attacker. We establish its connection to security of CPSs in the context of detecting the presence of malicious actuators (if any) in them. As primary contributions we establish necessary and sufficient conditions for the aforementioned detection in CPSs modeled as Markov decision processes (MDPs). Moreover, we focus on the mechanism of perturbing the pre-determined control policies of the honest agents in CPSs modeled as stochastic linear systems, by injecting a certain class of random process called private excitation; sufficient conditions for detectability and non-detectability of the presence of malicious actuators assuming that the policies are randomized history dependent and randomized Markovian, are established. Several technical aspects of our results are discussed extensively.