MIDS: A New Vehicle Intrusion Detection System Based on Multiple Features

Intelligent vehicles have become a typical representative of the next generation of technological developments, which provide users with convenient and comfortable driving experiences. However, owing to the factors in weak access control of communication interfaces, lack of authentication for data interaction, and no source/destination address for messages, the controller area network (CAN) is vulnerable to malicious attacks. Due to the resource constraints of bandwidth and the high requirement of real-time data transmission in CAN bus, security solutions, such as in-vehicle gateways and firewalls, cannot be endowed with complex encryption authentication algorithms, contributing to the limited capabilities in security protection. Therefore, some scholars proposed intrusion detection systems (IDSs) based on side-channel analysis. However, most of the existing detection models are based on single-class side-channel features to detect limited types of attacks. How to design a robust, lightweight, highly real-time, and traceable IDS is a major problem in the field of vehicle security. In view of this, we design a new IDS based on multiple features, called MIDS. We have conducted numerous experiments on two different brands of vehicles for three typical attacks, and MIDS has a detection accuracy of more than 98% and detects per frame within 0.12ms.