Detection and Mitigation of False Data Injection Attack (FDIA) on Load Frequency Control System

This article addresses the detection and mitigation of false data injection attacks (FDIA) in load frequency control (LFC) of a two-area interconnected power system using Kalman filtering and $\chi^{2}$ test. Kalman filters are employed for state estimation based on sensor data, while $\chi^{2}$ test assesses measurement consistency to identify anomalies indicative of false data. An adaptive correction technique is used to mitigate the impact of FDIA. This technique leverages the real-time response error between the normal and attacked system, to dynamically adjust the system behavior. Simulation results validate the method's effectiveness. This study provides a foundation for further research on advanced mitigation strategies. It also aims to develop and refine the detection framework for FDIA in LFC systems. ¹