Detecting integrity attacks on control systems using a moving target approach

Abstract

Maintaining the security of control systems in the presence of integrity attacks is a significant challenge. In literature, several possible attacks against control systems have been formulated including replay, false data injection, and zero dynamics attacks. The detection and prevention of these attacks may require the defender to possess a particular subset of trusted communication channels. Alternatively, these attacks can be prevented by keeping the system model secret from the adversary. In this paper, we consider an adversary who has the ability to modify and read all sensor and actuator channels. To thwart this adversary, we introduce external states dependent on the state of the control system, with linear timevarying dynamics unknown to the adversary. We also include sensors to measure these states. The presence of unknown timevarying dynamics is leveraged to detect an adversary who simultaneously aims to identify the system and inject stealthy outputs. Potential attack strategies and bounds on the attacker's performance are provided.

A moving target approach for identifying malicious sensors in control systems

“…Theorem 19: Consider the estimator of x k defined by (20), (21), (23), (24). Then lim sup k→∞ ∆e * k = ∞ =⇒ lim sup k→∞ ∆z i k = ∞ for some i ∈ {1, · · · , m}.…”

“…To meet this objective, we propose changing the dynamics of the system model in a time varying fashion, unknown to the adversary. A similar scheme is considered for the detection of integrity attacks in [23]. The time varying dynamics act like a moving target, preventing an information constrained adversary from developing stealthy unidentifiable attacks.…”

Joint attack detection and secure state estimation of cyber‐physical systems

“…Secure strategies have been studied for replay attacks [3], [4] where the adversary first records and then replays the observed data, as well as for denial-of-service (DoS) attacks [5], [6] disrupting the flow of data. Moreover, active detection methods have been designed in order to detect stealthy attacks via manipulation of, e.g., control inputs [7] or dynamics [8]. Over the last few years, the problem of secure state estimation, i.e.…”

A Moving Target Defense to Detect Stealthy Attacks in Cyber-Physical Systems

“…Several authors have proposed MTD approaches for state estimation in the smart grid [3]- [5], where the main idea consists on changing the physical topology of the power grid in order to reveal false data injection attacks. Watermarking uses the addition of an external system with linear time-varying dynamics that depend on the system states and that is unknown to the attacker [6]. The detection strategy measures those external states, making it harder for an adversary to design stealthy attacks.…”