Locating False Data Injection Attacks on Smart Grids Using D-FACTS Devices

Beibei Li, Qingyun Du, Jiarui Song, Aohan Li, Xiaoxia Ma

Abstract: In the context of Industry 4.0, the high-profile false data injection (FDI) attacks are posing increasing cyber threats to the reliability of smart grids. Recent studies have investigated the possibilities of detecting FDI attacks on smart grids by using the distributed flexible AC transmission system (D-FACTS) devices. However, few studies focus on further locating such cyber threats using D-FACTS devices. To meet this gap, we systematically explored such a topic and propose a graph theory based scheme to locate FDI attacks by employing D-FACTS devices, where both single-bus FDI attacks and multiple-bus FDI attacks are considered. Numerical results on the standard IEEE 14-bus system demonstrated that the proposed scheme can achieve 100% accuracy when locating any single-bus FDI attacks and most of the independent multiple-bus FDI attacks. Future potential solutions are also discussed to some special cases of multiple-bus FDI attacks that the proposed scheme cannot well handle.