Intrusion Detection System in Intelligent Connected Vehicles Based on Two-Step Algorithm

Tianyu Liu; Yongpei Jian; Tonghong Chong; Xu Lu; Pingyi Liu; Xianfeng Jia

doi:10.2991/978-94-6463-304-7_60

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Intrusion Detection System in Intelligent Connected Vehicles Based on Two-Step Algorithm

Authors

Tianyu Liu¹, Yongpei Jian¹^{, *}, Tonghong Chong¹, Xu Lu¹, Pingyi Liu¹, Xianfeng Jia¹

¹CATARC Intelligent and Connected Technology Co., LTd, Tianjin, 300000, China

^*Corresponding author. Email: jianyongpei@catarc.ac.cn

Corresponding Author

Yongpei Jian

Available Online 4 December 2023.

DOI: 10.2991/978-94-6463-304-7_60 How to use a DOI?
Keywords: Intrusion Detection System; Intelligent Connected Vehicles; Bayesian Network; Cybersecurity
Abstract: Intelligent connected vehicles are an inseparable object in the Internet of Things. The automotive industry is facing enormous challenges when it comes to ensuring the safety and reliability of vehicles. In this case, intelligent connected vehicle suppliers are committed to providing secure systems to ensure users' driving safety and protect them from possible cyberattacks. This article proposes an intrusion detection system based on an embedded environment suitable for intelligent connected vehicles. The two-step algorithm is used to detect possible attacks. To evaluate the performance of the system, this paper conducts experimental tests, calculates classic accuracy evaluation parameters, and compares them with simulated cyberattack data sets. The results show that this method has superior detection performance for common cyberattacks. When testing this method under a Free State attack, performance was degraded.
Copyright: © 2023 The Author(s)
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title: Proceedings of the 3rd International Conference on Digital Economy and Computer Application (DECA 2023)
Series: Atlantis Highlights in Computer Sciences
Publication Date: 4 December 2023
ISBN: 10.2991/978-94-6463-304-7_60
ISSN: 2589-4900
DOI: 10.2991/978-94-6463-304-7_60 How to use a DOI?
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

ris enw bib

TY  - CONF
AU  - Tianyu Liu
AU  - Yongpei Jian
AU  - Tonghong Chong
AU  - Xu Lu
AU  - Pingyi Liu
AU  - Xianfeng Jia
PY  - 2023
DA  - 2023/12/04
TI  - Intrusion Detection System in Intelligent Connected Vehicles Based on Two-Step Algorithm
BT  - Proceedings of the 3rd International Conference on Digital Economy and Computer Application (DECA 2023)
PB  - Atlantis Press
SP  - 574
EP  - 580
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-304-7_60
DO  - 10.2991/978-94-6463-304-7_60
ID  - Liu2023
ER  -

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