Journal
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
Volume 21, Issue 3, Pages 919-933Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TITS.2019.2908074
Keywords
Controller area network (CAN); cybersecurity; in-vehicle network (IVN); intrusion detection system (IDS); information entropy; machine learning
Categories
Funding
- National Key Research and Development Plan of China [2016YFB0200405]
- National Natural Science Foundation of China [61702172, 61672217, 61502405, 61370097, 61502162]
- Natural Science Foundation of Hunan Province, China [2018JJ3076, 2018JJ2063]
- China Postdoctoral Science Foundation [2016M592422]
- CCF-NSFOCUS Open Research Fund [CCF-NSFOCUS2018009]
- Fundamental Research Funds for the Central Universities
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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.
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