Novel SMO-Based Detection and Isolation of False Data Injection Attacks Against Frequency Control Systems

Abstract

The integration of modern power systems with information and communication technologies exposes them to various cyber threats. Load frequency control (LFC) is a communication-based automation in power systems that regulates the frequency of the grid. Its critical role makes it a highly attractive target for adversaries. This paper proposes a novel detection and isolation method of False Data Injection Attacks (FDIAs) against LFC. The defense method employs sliding mode observation techniques to detect FDIAs against LFC in real-time and discover which parts of the control loop have been compromised. Attacks are identified by comparing the generated residuals with a specific threshold that is designed in an adaptive manner. The proposed method is able to successfully distinguish the FDIAs from other system disturbances and is robust against uncertainties in power system parameters and noisy measurements. The effectiveness and scalability of the proposed defense method are confirmed on realistic power system models, considering nonlinearities, different topologies and diverse types of transmission links.