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Intrusion Detection in New Energy Vehicle Power Domains Based on Association Rules and Outlier Detection
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Chenyi YU1, Hongqian WEI1, 2, Youtong ZHANG1
Chinese Journal of Automotive Engineering | 2024, 14(3) : 412 - 421
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Chinese Journal of Automotive Engineering | 2024, 14(3): 412-421
• Intelligent Safety/Security Technologies and Test/Evaluation •
Intrusion Detection in New Energy Vehicle Power Domains Based on Association Rules and Outlier Detection
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Chenyi YU1, Hongqian WEI1, 2, Youtong ZHANG1
Affiliations
  • 1 School of Mechanical and Vehicular Engineering Beijing Institute of Technology Beijing 100081 China
  • 2 Vehicle Measurement, Control and Safety Key Laboratory of Sichuan Province Chengdu 610039 China
doi: 10.3969/j.issn.2095–1469.2024.03.09
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To improve the effectiveness of intrusion detection systems against tampering attacks in the power domain of new energy vehicles, a power domain protection model is established, including both association rule detection and outlier detection. By collecting the power domain messages from the actual vehicles and establishing a rule base using the association rule algorithm, this model aims to detect tampering attacks. On the basis of association rule detection, complex types of tampering attacks are identified through outlier detection. The simulation results show that this method improves the detection accuracy by 5.83% compared to traditional association rule methods, effectively detecting tampering attacks in the power domain of new energy vehicles.

automobile power domain  /  tampering attacks  /  intrusion detection systems  /  association rules  /  outlier detection
余辰熠, 魏洪乾, 张幽彤. 基于关联规则与离群点的新能源汽车动力域入侵检测. 汽车工程学报, 2024 , 14 (3) : 412 -421 . DOI: 10.3969/j.issn.2095–1469.2024.03.09
Chenyi YU, Hongqian WEI, Youtong ZHANG. Intrusion Detection in New Energy Vehicle Power Domains Based on Association Rules and Outlier Detection[J]. Chinese Journal of Automotive Engineering, 2024 , 14 (3) : 412 -421 . DOI: 10.3969/j.issn.2095–1469.2024.03.09
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Year 2024 volume 14 Issue 3
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doi: 10.3969/j.issn.2095–1469.2024.03.09
  • Receive Date：2023-03-21
  • Online Date：2025-07-21
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  • Received：2023-03-21
  • Revised：2023-04-19
Affiliations
    1 School of Mechanical and Vehicular Engineering Beijing Institute of Technology Beijing 100081 China
    2 Vehicle Measurement, Control and Safety Key Laboratory of Sichuan Province Chengdu 610039 China
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