Abstract
Smart grid integrates the physical power system infrastructure with internet-of-things-based digital communication networks that work together for grid stability, sustainability, and reli-ability. A significant number of smart devices converge in cyber-physical systems to make the smart grid more competitive and efficient in addressing the energy challenges and vulnerabilities in power system confidentiality, integrity, and availability in smart grid cyber-physical security systems. False data injection attacks are the most malicious threats in the smart grid paradigm and have been widely applied recently. Last few years, several detection algorithms for identi-fying the false data injection attack have been developed. Addressing these issues, this paper reports a false data injection attack and threat mathematical model, impacting the on-grid system, economy, and society. The classification of false data injection attack detection algorithms and mathematical models are mainly presented. Finally, issues and challenges are identified from existing research and recommended for future research direction.