摘要
为提高新能源汽车动力域中针对篡改攻击的入侵检测系统效果,建立包括关联规则检测和离群点检测的动力域防护模型,通过实车采集固定工况下的动力域报文数据,基于关联规则算法建立规则库检测篡改攻击;在关联规则检测的基础上通过离群点检测,检测复杂类型的篡改攻击。仿真结果表明,该方法相比于传统的关联规则方法检测准确率提高5.83%,能有效检测针对新能源汽车动力域的篡改攻击。
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.
作者
余辰熠
魏洪乾
张幽彤
YU Chenyi;WEI Hongqian;ZHANG Youtong(School of Mechanical and Vehicular Engineering,Beijing Institute of Technology,Beijing 100081,China;Vehicle Measurement,Control and Safety Key Laboratory of Sichuan Province,Chengdu 610039,China)
出处
《汽车工程学报》
2024年第3期412-421,共10页
Chinese Journal of Automotive Engineering
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
automobile power domain
tampering attacks
intrusion detection systems
association rules
outlier detection
