Security Threats & Attacks in IoV Environment: Open Research Issues and Challenges
Abstract
With advancement in technology, our lives have become safer, smarter and easier. There has been a large increase in number of vehicles connected to Internet. The rapid progress in technology has brought the concept of Internet of Vehicles (IoV) to real life. Networks involving Vehicle-to-Vehicle communication can be extended to IoV. With the help of AI knowledge of other cars and their activities, IoV helps to improve driving aids. IoV is the upgraded version of Vehicular Ad Hoc Networks (VANET), which was designed to provide safe driving. Due to lack of security, IoV environments might face threats from various attacks. There are a huge number of malicious attackers because of the self-organization and openness of IoV. Thus, the users of vehicles may face grave concern as whether the information received is genuine or not. In our paper, several attacks, threats and security aspects related to IoV paradigm has been discussed along with open issues and challenges faced by IoV environment.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
[73] examined security challenges of IoV, emphasizing attack types and need for privacy preservation and strong authentication, but without ML techniques.
“In [73], the author examined the security challenges of IoV environments, emphasizing various attack types and the need for privacy preservation and strong authentication, thereby contributing to discussions on security but without ML techniques.”
From Security and Trust Management in the Internet of Vehicles (IoV): Challenges and Machine Learning Solutions (2024) · cites this paper as [73]
Despite several surveys on IoV security, few surveys have covered ML-based solutions in security or trust schemes in this environment.
“Despite the fact that there are several surveys on IoV security [12,65,67,69,71,72,73,74,75], few surveys have covered ML-based solutions in security or in trust schemes in this environment.”
From Security and Trust Management in the Internet of Vehicles (IoV): Challenges and Machine Learning Solutions (2024) · cites this paper as [73]
Cites
Still being checked.
Cited by
Sorted by citations
Alalwany, E., & Mahgoub, I. (2024) · Sensors · doi:10.3390/s24020368 · Cited by 130 · see citing works
A Distributed Lightweight PUF-Based Mutual Authentication Protocol for IoV
Alkanhal, M., Alali, A., & Younis, M. (2023) · IoT · doi:10.3390/iot5010001 · Cited by 20 · see citing works
Yangyang, L. I. U., Xue, L., Wang, S., Luo, X., Zhao, K., Jing, P., Ma, X., Tang, Y., & Zhou, H. (2025) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2025.3567940 · Cited by 16 · see citing works
Enhancing Task Offloading in IoV With a Two-Stage Algorithm Under Information Asymmetry
Lu, Y., Zhang, G., Su, X., Wang, X., Huo, Y., & Jing, T. (2025) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2025.3553470 · Cited by 7 · see citing works
On the secure performance of Internet of Vehicles in Nakagami-m fading scenarios
Liu, Y., Yan, M., Wang, S., Pan, G., & An, J. (2023) · Physical Communication · doi:10.1016/j.phycom.2023.102111 · Cited by 4 · see citing works
Sykam, V. N. K., Goyal, A., Nijim, M., Mishra, A., & Hicks, D. (2024) · International Conference on Circuit, Systems and Communication (ICCSC) · doi:10.1109/iccsc62074.2024.10616984
A Comprehensive Survey on Blockchain-Based Security Mechanisms for the Internet of Vehicles
Mallat, S., Harrabi, S., & Jaâfar, I. B. (2026) · Journal of Network and Systems Management · doi:10.1007/s10922-026-10075-0
Physical Layer Key Generation for V2X Communications with Doppler Shift Compensation
Hou, W., Fu, H., & Peng, L. (2026) · International Conference on Communications · doi:10.1109/icc59461.2026.11587182
- Authors
- Garg, A., Chauhan, A., & Shambharkar, P. G.
- Affiliations
- Delhi Technological University (IN)
- Venue
- 2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT)
- Publisher
- IEEE
- Published
- 2022-08-11
- Pages
- 803-810
- OpenAlex
- W4312389652
- Cited by
- 8
- References
- 0
- Citations by year
- 2026: 2 · 2025: 2 · 2024: 2 · 2023: 2
- FWCI
- 2.43
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT) (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 › Engineering › Mechanical Engineering › IoT and GPS-based Vehicle Safety Systems
- Keywords
- Internet of Vehicles, vehicular networks, security threats, cyberattacks, vehicle-to-vehicle communication, vehicular ad hoc networks, malicious attackers, information authenticity, open problems
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review