A Survey of Intrusion Detection for In-Vehicle Networks

By Wufei Wu, Renfa Li, Guoqi Xie, Ji-yao An, Yang Bai, Jia Zhou, Keqin Li. IEEE transactions on intelligent transportation systems (Print), 2020

318 citations recorded by the source corpus.

The development of the complexity and connectivity of modern automobiles has caused a massive rise in the security risks of in-vehicle networks (IVNs). Nevertheless, existing IVN designs (e.g., controller area network) lack cybersecurity consideration. Intrusion detection, an effective method for defending against cyberattacks on IVNs while providing functional safety and real-time communication guarantees, aims to address this issue. Therefore, the necessity of its research has risen. In this paper, an IVN environment is introduced, and the constraints and characteristics of an intrusion detection system (IDS) design for IVNs are presented. A survey of the proposed IDS designs for the IVNs is conducted, and the corresponding drawbacks are highlighted. Various optimization objectives are considered and comprehensively compared. Lastly, the trend, open issues, and emerging research directions are described.

Subfields: Automotive Engineering, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/f97424b7026d344ccab301da4da81ef292a89aee

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