A Dynamic-Watermarking-Based Cyberattack Detection Framework on an LFC System With Uncertain Parameters

Abstract

The real-time control of modern power systems faces cyber risks owing to the deep coupling of cyber systems and physical systems. Attack detection plays an important role in cybersecurity issues. In load frequency control systems, for example, detecting whether malicious data are injected guarantees the stability of the frequency. As an effective active attack detection algorithm, the dynamic watermarking algorithm faces challenge of parameter uncertainty in real-world applications. Here, we quantitatively analyze the influence of uncertain parameters for the dynamic-watermarking-based detection algorithm. By introducing the parameter identification algorithm, we propose an active attack detection framework for LFC systems with uncertain parameters, which is constructed for an online application. The proposed framework is validated in a real-world three-region power system simulation. The results show that the introduction of the parameter identification steps ensures the validity of the detection algorithm and can effectively avoid the malfunction of the detection mechanism caused by uncertain parameters.