Review of False Data Injection Attacks in Power CPS: Challenges, Detection, and Resilience Strategies

The increasing integration of Cyber-Physical Systems (CPS) into power grids has significantly enhanced their efficiency and flexibility. However, this integration has also exposed power grids to emerging cyber threats, particularly False Data Injection Attacks (FDIAs), which can disrupt the operation of Power CPS by manipulating system data. This paper reviews the challenges, detection methods, and resilience strategies related to FDIAs in Power CPS. It provides an overview of the types of FDIAs, their impact on system security and stability, and the evolving nature of these attacks. It further examines recent advances in detection techniques, including machine learning, deep learning, and hybrid detection methods, as well as data reconstruction and attack localization strategies. The paper concludes by highlighting future research directions, emphasizing the need for a multi-faceted approach combining technical, regulatory, and operational measures to secure Power CPS against the growing threat of FDIAs.