Safeguarding the Future of Mobility: Cybersecurity Issues and Solutions for Infrastructure Associated with Electric Vehicle Charging

The development of an ecosystem that balances consumer convenience and security is imperative given the expanding market for electric vehicles (EVs). The vast amount of data that EV charging station management systems (EVCSMSs) give is powered by the Internet of Things (IoT) ecosystem. Intrusion Detection Systems (IDSs), which track network traffic to spot potentially dangerous data exchanges in IT and IoT contexts, are constantly improving in terms of efficacy and accuracy. Intrusion detection is becoming a major topic in academia because of the acceleration of IDS development caused by machine learning and deep learning techniques. The goal of the research presented in this paper is to use a machine-learning-based intrusion detection system with low false-positive rates and high accuracy to safeguard the ecosystem of EV charging stations (EVCS).

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Publication Details

Journal
European Journal of Engineering and Technology Research
Published
2025-03-19
DOI
https://doi.org/10.24018/ejeng.2025.10.2.3249
Citations
1
Primary Topic
Smart Grid Security and Resilience
Type
article
Field-Weighted Citation Impact
1.21
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article

Safeguarding the Future of Mobility: Cybersecurity Issues and Solutions for Infrastructure Associated with Electric Vehicle Charging

João Paulo da Silveira Nogueira Lima, Alison Holmes, Md Rakibul Karim Akanda, Christina Bonner
1 citations
European Journal of Engineering and Technology Research
Smart Grid Security and Resilience
1.21
article

Safeguarding the Future of Mobility: Cybersecurity Issues and Solutions for Infrastructure Associated with Electric Vehicle Charging

João Paulo da Silveira Nogueira Lima, Alison Holmes, Md Rakibul Karim Akanda, Christina Bonner
article en
1 citations

Abstract

The development of an ecosystem that balances consumer convenience and security is imperative given the expanding market for electric vehicles (EVs). The vast amount of data that EV charging station management systems (EVCSMSs) give is powered by the Internet of Things (IoT) ecosystem. Intrusion Detection Systems (IDSs), which track network traffic to spot potentially dangerous data exchanges in IT and IoT contexts, are constantly improving in terms of efficacy and accuracy. Intrusion detection is becoming a major topic in academia because of the acceleration of IDS development caused by machine learning and deep learning techniques. The goal of the research presented in this paper is to use a machine-learning-based intrusion detection system with low false-positive rates and high accuracy to safeguard the ecosystem of EV charging stations (EVCS).

European Journal of Engineering and Technology ResearchVol. 10(2)
Savannah State University (US)
Openalex Percentile: Top 23%
Smart Grid Security and Resilience
1.21
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