Autoregressive watermark detection and basis function regression defense scheme for FDIA on multi-area interconnected power systems

Abstract

This paper investigates the problem of false data injection attack (FDIA) detection and defense for multi-area interconnected power systems. The measurement data upload and control command delivery channels in such systems are vulnerable to cyber attacks. To address the issues of high false alarm rates and detection delays in traditional detection methods, we propose a watermark-based detection method using an autoregressive model and a basis function regression defense strategy. This method can reduce detection delay and demonstrate higher detection accuracy under various attack strategies. Based on the capabilities of attackers, we have constructed three attack strategies. The effectiveness of the proposed detection method has been verified. Furthermore, a basis function regression defense strategy is proposed to enhance system stability by mitigating attack intensity. Simulation results verify the superiority of our detection method over ${\chi }^2$ detection and fast attack detection, while demonstrating that the proposed defense scheme maintains stable system operation during attacks.