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Lookup NU author(s): Dr Dev JhaORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2026 The Author(s). IET Intelligent Transport Systems published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology. The market penetration of electric vehicles (EV) has increased globally due to their proven efficiency, sustainability and government support. EV adoption has accelerated the demand for accessible and reliable EV charging infrastructure. Existing literature highlights the increasing demand for EV and emphasises the critical importance of securing EV charging infrastructure. However, there is a lack of security measures in place for analysing, detecting and mitigating cyber-attacks on EV charging infrastructure. In this context, this paper explores the security aspects of an EV charging management and security (EVCMS) framework. The paper examines the impact of denial of service (DoS) attacks on EVCMS services, focusing on Slow DoS attacks and their mitigation. Employing the SlowHTTPtest tool for generating attack traffic and Wireshark for in-depth analysis, we have explored four types of Slow DoS attacks targeting HTTPS applications within the EVCMS framework. The packet traffic pattern was scrutinised with a focus on packet window size and delta time to detect signs of Slow DoS attacks. Subsequently, a mitigation strategy is proposed involving the implementation of custom detection rules in Suricata. These rules are intended to trigger alerts upon detecting DoS attacks in the EVCMS framework. The performance evaluation demonstrates that the proposed detection and mitigation strategy is capable of blocking the attacker's IP address and directing it to iptables for further action. This strategy enhances the EVCMS framework's resilience against such cyber attacks, ensuring reliable and secure EV charging services to users. The novelty of this work lies in correlating network-layer metrics (window size and delta time) to detect Slow DoS attack patterns and applying a Suricata–iptables synergy tailored specifically for EVCMS contexts.
Author(s): Hamdare S, Brown D, Jha DN, Aljaidi M, Khasawneh AM, Cao Y, Kumar S, Saied O, Jugran M, Kaiwartya O
Publication type: Article
Publication status: Published
Journal: IET Intelligent Transport Systems
Year: 2026
Volume: 20
Issue: 1
Online publication date: 20/08/2026
Acceptance date: 08/07/2026
Date deposited: 01/09/2026
ISSN (print): 1751-956X
ISSN (electronic): 1751-9578
Publisher: John Wiley and Sons Inc.
URL: https://doi.org/10.1049/itr2.70306
DOI: 10.1049/itr2.70306
Data Access Statement: The data that support the findings of this study are available from the corresponding author upon reasonable request.
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