关键词: 车载 CAN 总线；网络安全；安全防护技术；相对熵；机器学习

Abstract: It is well known that controller area network (CAN) is the most widely used bus, whose advantages are low cost, strong anti-interference and supporting distributed serial communication. Unfortunately, the ineradicable security flaws have been investigated such as no authentication, no encryption and multiple remote connection ports, and thus it is the main target of hacker attack. In this paper, the recent automobile network security accidents may be reviewed at first, and relevant intrusion types are listed, in which the replay and discard are the most common attack methods.Then, the causes of CAN bus vulnerability will be analyzed, and the corresponding solutions are offered simultaneously. Finally, the information entropy and relative entropy are applied to detect the illegal intrusion, and the results have been simulated by CANoe software, showing the outstanding validity. In fact, eliminating illegal network intrusion is so tough that further research is needed under controller area network with flexible data-rate (CAN-FD) new frameworks to satisfy higher requirement such as security and real-time performance in future.

Key words: Vehicle CAN bus; Cybersecurity; Safety protection technology; Relative entropy; Machine learning