Jing Guo*, Ziying Wang, Yajuan Guo, Haitao Jiang
CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 427-442, 2025, DOI:10.32604/cmc.2024.057045
- 03 January 2025
Abstract The rapid proliferation of electric vehicle (EV) charging infrastructure introduces critical cybersecurity vulnerabilities to power grids system. This study presents an innovative anomaly detection framework for EV charging stations, addressing the unique challenges posed by third-party aggregation platforms. Our approach integrates node equations-based on the parameter identification with a novel deep learning model, xDeepCIN, to detect abnormal data reporting indicative of aggregation attacks. We employ a graph-theoretic approach to model EV charging networks and utilize Markov Chain Monte Carlo techniques for accurate parameter estimation. The xDeepCIN model, incorporating a Compressed Interaction Network, has the ability… More >
Login
Register
