A Trust Model for Edge-Driven Vehicular Ad Hoc Networks Using Fuzzy Logic

Hasan, Md Mahmudul; Jahan, Mosarrat; Kabir, Shaily

Abstract

Trust establishment among vehicles is essential for vehicular ad hoc networks (VANETs) as it directly impacts the security and privacy of vehicular communication. Many trust estimation approaches have been introduced, however, they often suffer from ensuring effective trust for vehicles. In fact, existing approaches do not involve all malevolent properties of vehicles in trust computation and can not properly handle the content tampering attack, which eventually affect the accuracy of the estimated trust. Moreover, most of them do not consider the uncertainty of VANET arising from vehicles' mobility, their inaccurate/incomplete data dissemination, and the wireless communication channels, which also affects the reliability of the trust estimation. To address these limitations, this paper proposes a fuzzy logic-based approach to estimate vehicles' trust. The new approach considers three trust factors, captured by fuzzy sets, to model malicious properties of a vehicle. Further, it involves a new data-centric parameter to capture the impact of content tampering on trust evaluation. In addition, the new approach includes an inter-edge trust transfer mechanism to carry forward a vehicle's trust when it switches to a new edge server to ensure a seamless operation in VANETs. We evaluate the performance of the proposed scheme against the state-of-the-art approaches using both synthetic and real-world datasets. The experimental results reveal that it outperforms existing schemes in detecting malicious vehicles with higher recall, precision, and accuracy. Further, the new scheme reduces end-to-end delay and messages per data packet compared to other schemes.

Citation

Hasan, M. M., Jahan, M., & Kabir, S. (2023). A Trust Model for Edge-Driven Vehicular Ad Hoc Networks Using Fuzzy Logic. IEEE Transactions on Intelligent Transportation Systems, 24(12), 14037-14050. https://doi.org/10.1109/tits.2023.3305342

• Journal Article Type: Article
• Acceptance Date: Aug 4, 2023
• Online Publication Date: Sep 11, 2023
• Publication Date: 2023-12
• Deposit Date: Feb 28, 2025
• Publicly Available Date: Mar 13, 2025
• Journal: IEEE Transactions on Intelligent Transportation Systems
• Print ISSN: 1524-9050
• Electronic ISSN: 1558-0016
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 24
• Issue: 12
• Pages: 14037-14050
• DOI: https://doi.org/10.1109/tits.2023.3305342
• Public URL: https://nottingham-repository.worktribe.com/output/45861698
• Publisher URL: https://ieeexplore.ieee.org/document/10247089