| Title | A Hierarchical Attack Identification Method for Nonlinear Systems |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Braun, Sarah, Albrecht, Sebastian, Lucia, Sergio |
| Conference Name | 2020 59th IEEE Conference on Decision and Control (CDC) |
| Date Published | dec |
| Keywords | Computational modeling, Couplings, Decentralized control, Mathematical model, Nonlinear dynamical systems, Power system dynamics, pubcrawl, resilience, Resiliency, Sensitivity, System recovery |
| 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. |
| DOI | 10.1109/CDC42340.2020.9304231 |
| Citation Key | braun_hierarchical_2020 |
A Hierarchical Attack Identification Method for Nonlinear Systems