On the use of watermark-based schemes to detect cyber-physical attacks

Abstract

We address security issues in cyber-physical systems (CPSs). We focus on the detection of attacks against cyber-physical systems. Attacks against these systems shall be handled both in terms of safety and security. Networked-control technologies imposed by industrial standards already cover the safety dimension. However, from a security standpoint, using only cyber information to analyze the security of a cyber-physical system is not enough, since the physical malicious actions that can threaten the correct behavior of the systems are ignored. For this reason, the systems have to be protected from threats to their cyber and physical layers. Some authors have handled replay and integrity attacks using, for example, physical attestation to validate the cyber process and to detect the attacks, or watermark-based detectors which uses also physical parameters to ensure the cyber layers. We reexamine the effectiveness of a stationary watermark-based detector. We show that this approach only detects adversaries that do not attempt to get any knowledge about the system dynamics. We analyze the detection ratio of the original design under the presence of new adversaries that are able to infer the system dynamics and are able to evade the detector with high frequency. We propose a new detection scheme which employs several non-stationary watermarks. We validate the detection efficiency of the new strategy via numeric simulations and via running experiments on a laboratory testbed. Results show that the proposed strategy is able to detect adversaries using non-parametric methods, but it is not equally effective against adversaries using parametric identification methods.

Cyber‐physical architecture assisted by programmable networking

“…Notice that such anomalies can either be unintentional failures, or stealthy attacks disguised by intentional modifications produced by a malicious entity that intends to disrupt the physical system. Assuming a system with appropriate measure to detect both failures and attacks, the PN controller can react to those anomalies, by enforcing some mitigation policies. At the data domain, we have network probes and effectors , conducting data monitoring—if instructed by the control domain.…”

A Bernoulli-Gaussian physical watermark for detecting integrity attacks in control systems

“…In the case of Watermark 1, L m|b = L (m) , η v k follows a Markovian process (10) with parameters α and β and ∆u v k ∼ N (0, Q) is an IID Gaussian process. In the case of Watermark 2, L m|b = L (b) , η v k is an IID Bernoulli process with drop probability p d and ∆u v k is a stationary Gaussian process which satisfies (14). Additionally, v v k ∼ N (0, R) and w v k ∼ N (0, Q) are IID processes.…”

“…We now investigate a watermark consisting of stationary Gaussian noise generated by a HMM (14) and an IID Bernoulli drop process at the control input with drop probability equal to p d . Again, we design a watermark to address a performance and security trade-off.…”

“…Additionally, in a scalar setting, [13] demonstrates the optimality of Gaussian watermarks against Gaussian attackers and vice versa. [14] evaluates the use of non-stationary watermarks to hamper system identification. Finally, [15] considers watermarks to thwart adversaries who have access to a subset of inputs and model knowledge.…”

Detecting Integrity Attacks in IoT-based Cyber Physical Systems: a Case Study on Hydra Testbed

“…If data modification is not timely detected, it may result in severe disruption of the system or even in its complete damage. Badly secured IIoT structures and services may be used as entry points for network attacks and expose both data and systems to threats [3][4][5].…”