In-Vehicle Network Attacks and Countermeasures: Challenges and Future Directions
Abstract
The emergence of in-vehicle networks, which are composed of controller area network (CAN) buses and a great number of ECUs, significantly reduces the difficulty of vehicle designing, repairing and refitting. While owing to the intrinsic vulnerabilities of in-vehicle networks and the increasingly rich interfaces to connect in-vehicle networks to the outside, adversarial attacks can be easily implemented on in-vehicle networks. Such attacks cause serious threats to automobile security and drivers' privacy. In light of this, we provide in this article a detailed guidance, explain the basic concepts, introduce the vulnerabilities of in-vehicle networks, and summarize the attacking methodologies. We also provide countermeasures for in-vehicle networks and point out challenges and future directions.
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VANETs connected to the Internet are endangered by growing versatile attacks.
“As the vehicles are connected to Internet, these intelligent networks are endangered by the growing versatile attacks [6][7][8][9].”
From X-GEVON- a novel explainable intelligent network to detect the multiple attacks in vanet systems (2025) · cites this paper as [6]
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Ashraf, J., Bakhshi, A. D., Moustafa, N., Khurshid, H., Javed, A., & Beheshti, A. (2021) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2020.3017882 · Cited by 295 · see citing works
Internet of Things: Evolution, Concerns and Security Challenges
Malhotra, P., Singh, Y., Anand, P., Bangotra, D. K., Singh, P. K., & Hong, W.-C. (2021) · Sensors · doi:10.3390/s21051809 · Cited by 260 · see citing works
When Machine Learning Meets Privacy in 6G: A Survey
Sun, Y., Liu, J., Wang, J., Cao, Y., & Kato, N. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2020.3011561 · Cited by 211 · see citing works
Self-citationAnand, P., Singh, Y., Selwal, A., Singh, P. K., Felseghi, R. A., & Raboaca, M. S. (2020) · Energies · doi:10.3390/en13184813 · Cited by 72 · see citing works
X-GEVON- a novel explainable intelligent network to detect the multiple attacks in vanet systems
Anjali, T., Goyal, R., & Balaji, G. N. (2025) · Discover Computing · doi:10.1007/s10791-025-09696-x · Cited by 6 · see citing works
- Authors
- Liu, J., Zhang, S., Sun, W., & Shi, Y.
- Affiliations
- Xidian University (CN)
- Venue
- IEEE Network
- Published
- 2017
- Volume
- 31
- Issue
- 5
- Pages
- 50-58
- ISSN
- 0890-8044 (ISSN-L)
- OpenAlex
- W2759891682
- Cited by
- 281
- References
- 0
- Citations by year
- 2026: 16 · 2025: 37 · 2024: 42 · 2023: 34 · 2022: 37 · 2021: 44 · 2020: 35 · 2019: 16 · 2018: 20
- FWCI
- 8.07
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Network (publishedVersion)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Vehicular Ad Hoc Networks (VANETs)
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Security and Intrusion Detection
- Physical Sciences › Computer Science › Artificial Intelligence › Security and Verification in Computing
- Keywords
- in-vehicle networks, automotive cybersecurity, CAN bus, electronic control units, network vulnerability, adversarial attacks, countermeasures, driver privacy, connected vehicles
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