Vehicular Intrusion Detection System for Controller Area Network: A Comprehensive Survey and Evaluation
The progress of automotive technologies has made cybersecurity a crucial focus, leading to various cyber attacks. These attacks primarily target the Controller Area Network (CAN) and specialized Electronic Control Units (ECUs). In order to mitigate these attacks and bolster the security of vehicular systems, numerous defense solutions have been proposed. These solutions aim to detect diverse forms of vehicular attacks. However, the practical implementation of these solutions still presents certain limitations and challenges. In light of these circumstances, this paper undertakes a thorough examination of existing vehicular attacks and defense strategies employed against the CAN and ECUs. The objective is to provide valuable insights and inform the future design of Vehicular Intrusion Detection Systems (VIDS). The findings of our investigation reveal that the examined VIDS primarily concentrate on particular categories of attacks, neglecting the broader spectrum of potential threats. Moreover, we provide a comprehensive overview of the significant challenges encountered in implementing a robust and feasible VIDS. Additionally, we put forth several defense recommendations based on our study findings, aiming to inform and guide the future design of VIDS in the context of vehicular security.
Authors
- Xiaobo Ma (ORCID: https://orcid.org/0000-0002-0934-5035)
- Pengfei Jing (ORCID: https://orcid.org/0000-0002-2380-1447)
- Sishan Wang (ORCID: https://orcid.org/0000-0001-6757-8112)
- Lei Xue (ORCID: https://orcid.org/0009-0003-1952-885X)
- Xiapu Luo (ORCID: https://orcid.org/0000-0002-9082-3208)
- Kaifa Zhao (ORCID: https://orcid.org/0000-0002-3102-7498)
- Haiying Zhou (ORCID: https://orcid.org/0000-0002-3637-9652)
- Yajuan Tang (ORCID: https://orcid.org/0000-0002-8741-2934)
- Yangyang Liu (ORCID: https://orcid.org/0000-0001-5792-5491)
Institutions
- Hong Kong Polytechnic University (HK)
- Sun Yat-sen University (CN)
- Shantou University (CN)
- Hubei University of Automotive Technology (CN)
- Xi'an Jiaotong University (CN)
Publication Details
- Journal
- IEEE Transactions on Intelligent Transportation Systems
- Published
- 2025-05-16
- DOI
- https://doi.org/10.1109/tits.2025.3567940
- Citations
- 5
- Primary Topic
- Network Security and Intrusion Detection
- Type
- article
- Field-Weighted Citation Impact
- 7.44