Reghunath, Rinith (2025) Advancing Cybersecurity in EV Charging Infrastructure: Vulnerabilities, Attacks, and a Real-time Monitoring and Detection Platform. Masters thesis, Concordia University.
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Abstract
Electric Vehicles (EVs) have gained significant popularity as a sustainable alternative to traditional vehicles, leading to the rapid deployment of EV Charging Stations (CSs). While vulnerabilities have been discovered in CSs with remote management portals, those requiring physical access are considered secure and have received less attention. This thesis introduces the first attack framework targeting these CSs that require physical access to operate their local management portal. By testing six real-world CSs deployed across North America and Europe, the thesis demonstrates how attackers can exploit design flaws to escalate privileges, manipulate configurations, and launch attacks that disrupt the power grid, enable financial fraud, and compromise charging infrastructure availability. In response to these vulnerabilities and cyberattack threats, the research develops EV-Shield, a real-time monitoring platform that collects and correlates data from multiple EV ecosystem components including CSs and the EV Charging Station Management System (CSMS). The platform is integrated with HydraEV, a distributed anomaly detection module that enables attack detection through its local and central detectors. By incorporating Smart Meters (SMs) as a novel monitoring component, EV-Shield enhances its resilience, ensuring reliable detection even when other data sources are compromised. The platform's performance is evaluated through multiple attack scenarios, demonstrating its effectiveness in safeguarding the public EV charging infrastructure. This thesis addresses critical security challenges in the rapidly evolving EV ecosystem, focusing on CS vulnerabilities and developing a real-time monitoring platform to detect cyberattacks. The goal is to ensure the safe and reliable expansion of EV infrastructure amid growing cybersecurity threats.
Divisions: | Concordia University > Gina Cody School of Engineering and Computer Science > Electrical and Computer Engineering |
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Item Type: | Thesis (Masters) |
Authors: | Reghunath, Rinith |
Institution: | Concordia University |
Degree Name: | M.A. Sc. |
Program: | Electrical and Computer Engineering |
Date: | 12 February 2025 |
Thesis Supervisor(s): | Assi, Chadi |
Keywords: | Electric vehicles, Cybersecurity, Attack detection, Grid stability, Security monitoring, Network and System Management |
ID Code: | 995109 |
Deposited By: | Rinith Reghunath |
Deposited On: | 17 Jun 2025 17:24 |
Last Modified: | 17 Jun 2025 17:24 |
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