查看文章

The interdependence of power and electrified transportation systems introduces new challenges to the reliability and resilience of charging infrastructure. With the increasing prevalence of electric vehicles (EVs), power system attacks that can lower customers charging satisfaction rates are on the rise. The existing false data injection attacks (FDIAs) detection strategies are not suitable for protecting the power-dependent transportation infrastructure since (a) these detectors are primarily optimized for power grids alone, and (b) they overlook the impact of attacks on the quality-of-service of EVs and charging stations (CSs). In response to these challenges, this paper aims to develop an FDIA detection strategy that takes advantage of the data correlations between power and transportation systems, ultimately enhancing the charging satisfaction rate. To achieve this goal, we propose a graph autoencoder-based FDIA …