汽车工程学报2024，Vol.14Issue(3)：412-421,10.DOI:10.3969/j.issn.2095‒1469.2024.03.09
基于关联规则与离群点的新能源汽车动力域入侵检测
Intrusion Detection in New Energy Vehicle Power Domains Based on Association Rules and Outlier Detection
余辰熠 1魏洪乾 2张幽彤1
作者信息
- 1. 北京理工大学 机械与车辆学院,北京 100081
- 2. 北京理工大学 机械与车辆学院,北京 100081||汽车测控与安全四川省重点实验室,成都 610039
- 折叠
摘要
Abstract
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.关键词
动力域/篡改攻击/入侵检测系统/关联规则/离群点检测Key words
automobile power domain/tampering attacks/intrusion detection systems/association rules/outlier detection分类
交通工程引用本文复制引用
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[J].汽车工程学报,2024,14(3):412-421,10.
