A Hierarchical Attack Identification Method for Nonlinear Systems

TL;DR

This paper presents a theoretical analysis and validation of a hierarchical attack identification method for large-scale nonlinear control systems, ensuring accurate detection of compromised components without global system knowledge.

Contribution

It provides rigorous sufficient conditions for attack identification in nonlinear systems and demonstrates practical applicability through numerical experiments.

Findings

Guarantees for attack identification under certain conditions

Applicable to large-scale nonlinear systems

Validated with IEEE 30 bus power system simulations

Abstract

Many autonomous control systems are frequently exposed to attacks, so methods for attack identification are crucial for a safe operation. To preserve the privacy of the subsystems and achieve scalability in large-scale systems, identification algorithms should not require global model knowledge. We analyze a previously presented method for hierarchical attack identification, that is embedded in a distributed control setup for systems of systems with coupled nonlinear dynamics. It is based on the exchange of local sensitivity information and ideas from sparse signal recovery. In this paper, we prove sufficient conditions under which the method is guaranteed to identify all components affected by some unknown attack. Even though a general class of nonlinear dynamic systems is considered, our rigorous theoretical guarantees are applicable to practically relevant examples, which is underlined by numerical experiments with the IEEE~30 bus power system.