汽车工程 ›› 2021, Vol. 43 ›› Issue (10): 1543-1548.doi: 10.19562/j.chinasae.qcgc.2021.10.017

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基于熵的车载CAN总线异常检测研究

张海春1,姜荣帅1,王颉2,鲁赵骏3,刘政林1()   

  1. 1.华中科技大学光学与电子信息学院,武汉 430074
    2.深圳开源互联网安全技术有限公司,深圳 518000
    3.华中科技大学网络空间安全学院,武汉 430074
  • 收稿日期:2021-04-19 修回日期:2021-05-25 出版日期:2021-10-25 发布日期:2021-10-25
  • 通讯作者: 刘政林 E-mail:liuzhenglin@hust.edu.cn
  • 基金资助:
    国家自然科学基金(61874047);深圳市创新创业专项—技术攻关面上项目(202011023000308)

Research on Anomaly Detection of In⁃Vehicle CAN Bus Based on Entropy

Haichun Zhang1,Rongshuai Jiang1,Jie Wang2,Zhaojun Lu3,Zhenglin Liu1()   

  1. 1.School of Optical and Electronic Information,Huazhong University of Science and Technology,Wuhan 430074
    2.Shenzhen Kaiyuan Internet Security Technology Co. ,Ltd. ,Shenzhen 518000
    3.School of Cyber Science and Engineering,Huazhong University of Science and Technology,Wuhan 430074
  • Received:2021-04-19 Revised:2021-05-25 Online:2021-10-25 Published:2021-10-25
  • Contact: Zhenglin Liu E-mail:liuzhenglin@hust.edu.cn

摘要:

由于缺乏加密、完整性校验和身份认证机制,车载CAN总线容易遭受攻击而造成总线数据帧流量异常。为检测攻击者注入车载CAN总线的异常数据帧流量,本文中在分析了基于信息熵的车载CAN总线异常检测机制的基础上,提出了基于相对熵的车载CAN总线异常检测机制,弥补了前者无法检测出异常细节信息的缺陷。在某型号福特车辆上的实验结果表明,基于相对熵的车载CAN总线异常检测机制不仅可以检测出DoS攻击、重放攻击造成的总线数据帧流量异常,还可以检测出具体的攻击类型和异常数据帧的ID,并且取得了较高的检测效率。

关键词: 车载CAN总线, 相对熵, 信息熵, 异常检测

Abstract:

Due to lack of encryption, integrity verification, and identity authentication mechanism, the vehicle Controller Area Network (CAN) bus is prone to attacks that cause abnormal bus data frame flow. In order to detect the abnormal data frame traffic injected by the attacker into the vehicle CAN bus, this paper analyzes the vehicle CAN bus anomaly detection mechanism based on information entropy, and proposes a vehicle CAN bus anomaly detection mechanism based on relative entropy, which makes up for the former's defect of inability to detect abnormal details of the defect. The experimental results on a certain Ford vehicle show that the CAN bus anomaly detection mechanism based on relative entropy can not only detect the abnormal flow of bus data frames caused by DoS attacks and replay attacks, but also detect specific attack types and abnormal CAN ID of the frame, with high detection efficiency.

Key words: in?vehicle CAN bus, relative entropy, information entropy, anomaly detection