Set-Theoretic Detection of Bias Injection Cyber-Attacks on Networked Power Systems
| Autor: | Leonidas Dritsas, Anthony Tzes, Efstathios Kontouras |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
0209 industrial biotechnology
Automatic Generation Control Computer science 020209 energy Detector Real-time computing State vector 02 engineering and technology Electric power system 020901 industrial engineering & automation Robustness (computer science) 0202 electrical engineering electronic engineering information engineering Attack patterns Invariant (mathematics) Computer Science::Cryptography and Security |
| Zdroj: | ACC |
| DOI: | 10.23919/acc.2018.8431469 |
| Popis: | This paper addresses the concept of a set-theoretic framework for the detection of bias injection cyber-attacks on the load frequency control loop of a networked power system. The proposed attack detection mechanism is based on the use of convex and compact polyhedral robust invariant sets. An alarm signal is triggered whenever the state vector exits the invariant sets, indicating a potential security breach. The attack scenario studied involves the transmission of corrupted frequency sensor measurements to the automatic generation control unit of a compromised control area. Simulation studies demonstrate the ability of a set-theoretic detector to disclose intermittent attack patterns even in the presence of disturbances. |
| Databáze: | OpenAIRE |
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