Cybersecurity in vehicle-to-grid (V2G) systems: A systematic review

Integrating electric vehicles (EVs) into the smart grid networks through vehicle-to-grid (V2G) systems offers transformative potential for energy optimisation and grid stability. However, this bidirectional energy exchange introduces significant cybersecurity challenges, including vulnerabilities to spoofing, denial-of-service attacks, and data manipulation, which threaten the integrity and reliability of the V2G system. Despite the growing body of research on V2G cybersecurity, existing studies often adopt fragmented approaches, leaving gaps in addressing the entire ecosystem, including users, EVs, charging stations, and energy market and trading platforms. This paper presents a systematic review of recent advancements in V2G cybersecurity, employing the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework for detailed searches across three journal databases and includes only peer-reviewed studies published between 2020 and 2024 (June). We identified and reviewed 134 V2G cybersecurity studies and found five important insights into existing V2G cybersecurity research. First, most studies (104 of 134) focused on protecting V2G systems against cyber threats, while only seven studies addressed the recovery aspect of the CRML (Cybersecurity Risk Management Lifecycle) function. Second, existing studies have adequately addressed the security of EVs and EVCS (EV charging stations) in V2G systems (113 and 81 of 134 studies, respectively). However, none have focused on the linkage between the behaviour of EV users and the cybersecurity of V2G systems. Third, physical access, control-related vulnerabilities, and user behaviour-related attacks in V2G systems are not addressed significantly. Furthermore, existing studies overlook vulnerabilities and attacks specific to AI (artificial intelligence) and blockchain technologies. Fourth, blockchain, AI, encryption, control theory, and optimisation are the main technologies used, and finally, the inclusion of quantum safety within encryption and AI models and AI assurance (AIA) is in a very early stage; only two and one of 134 studies explicitly addressed quantum safety and AIA through explainability. By providing a holistic perspective, this study identifies critical research gaps and outlines future directions for developing robust end-to-end cybersecurity solutions to safeguard V2G systems and support global sustainability goals.