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Enhancing V2G Network Security: A Novel Cockroach Behavior-Based Machine Learning Classifier to Mitigate MitM and DoS AttacksMEKKAOUI, K.   |
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Author keywords
electric vehicles, smart grids, intrusion detection, supervised learning, communication networks
References keywords
detection(11), intrusion(10), vehicle(9), security(7), electronics(7), review(6), networks(6), network(6), learning(6), internet(6)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2024-05-31
Volume 24, Issue 2, Year 2024, On page(s): 31 - 40
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2024.02004
Web of Science Accession Number: 001242091800004
SCOPUS ID: 85195631972
Abstract
V2G (Vehicle-to-Grid) is a system that allows an electric vehicle to connect and exchange energy with the electricity grid. This system is part of the smart-grid, which is an intelligent electricity network offering bidirectional communication and contributes to the environmental protection. Different actors are involved in communication in a V2G network, such as electric vehicles, charging stations, energy suppliers, and network operators, etc. Therefore, the V2G network faces several security challenges, such as data integrity, power system security, physical security of charging systems, data confidentiality and system interoperability. In this paper, an intrusion detection system (IDS) is proposed with the aim of predicting attacks in the V2G network. The study started with the generation of a dataset and the implementation of the Cockroach Behavior-Based Machine Learning Classifier with the objective of enhancing security of V2G networks by addressing Men-in-the-Middle (MitM) and Denial of Service (DoS) attacks. The simulation results, through the MiniV2G simulator, show that the proposed system achieved a detection accuracy of 98.93 %. This improves the reliability of the V2G network for users and better protects Electric Vehicle Charging Stations (EVCS) against DoS and MitM. |
| References | | | Cited By «-- Click to see who has cited this paper |
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.
Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.
