A Survey of Intrusion Detection for In-Vehicle Networks

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 de...

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Vydané v:IEEE transactions on intelligent transportation systems Ročník 21; číslo 3; s. 919 - 933
Hlavní autori: Wu, Wufei, Li, Renfa, Xie, Guoqi, An, Jiyao, Bai, Yang, Zhou, Jia, Li, Keqin
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 01.03.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Automobiles
Automotive engineering
Communication system security
Computer security
Control systems design
Controller area network
Controller area network (CAN)
Cybersecurity
In vehicle
in-vehicle network (IVN)
information entropy
Intrusion detection
intrusion detection system (IDS)
Intrusion detection systems
machine learning
Optimization
Safety
ISSN:1524-9050, 1558-0016
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Popis
Shrnutí: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.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1524-9050
1558-0016
DOI:10.1109/TITS.2019.2908074