Cyber-Attack Event Analysis for EV Charging Stations

TL;DR

This paper introduces a 5Ws & 1H investigation approach and a stochastic anomaly detection system to analyze and respond to cyber-attacks on electric vehicle charging stations, enhancing cybersecurity in smart transportation.

Contribution

It proposes a novel investigation framework and anomaly detection system specifically designed for cyber-attack analysis on EV charging stations.

Findings

The 5Ws & 1H approach improves incident understanding.

The stochastic ADS effectively detects anomalies post-attack.

Enhanced cybersecurity measures for EVCSs are achieved.

Abstract

Safe and secure electric vehicle charging stations (EVCSs) are important in smart transportation infrastructure. The prevalence of EVCSs has rapidly increased over time in response to the rising demand for EV charging. However, developments in information and communication technologies (ICT) have made the cyber-physical system (CPS) of EVCSs susceptible to cyber-attacks, which might destabilize the infrastructure of the electric grid as well as the environment for charging. This study suggests a 5Ws \& 1H-based investigation approach to deal with cyber-attack-related incidents due to the incapacity of the current investigation frameworks to comprehend and handle these mishaps. Also, a stochastic anomaly detection system (ADS) is proposed to identify the anomalies, abnormal activities, and unusual operations of the station entities as a post cyber event analysis.