Appeal-Based Distributed Trust Management Model in VANETs Concerning Untrustworthy RSUs

Wang, Y., Zhang, Y.’a., Song, Y., Cao, Y., Zhang, L. and Ren, X. (2023) Appeal-Based Distributed Trust Management Model in VANETs Concerning Untrustworthy RSUs. In: IEEE Wireless Communications and Networking Conference (WCNC2023), Glasgow, Scotland, UK, 26-29 March 2023, ISBN 9781665491228 (doi: 10.1109/WCNC55385.2023.10118674)

Abstract

Vehicular Ad-hoc Networks (VANETs) play an essential role in traffic safety and travel efficiency. However, due to the variable network topology of VANETs, malicious vehicles can easily invade the network to disrupt the network integrity. Moreover, compromised Roadside Units (RSUs) may pose a tremendous threat to network. Thus, we propose a distributed trust model to resist malicious vehicles and compromised RSUs by a mutual supervision mechanism between vehicles and RSUs. Three stages of this model ensure the trustworthiness of participants, including trust evaluation, adjudication, and vehicle appeal mechanism. In the trust evaluation stage, message receivers calculate three types of trust values (i.e., direct, indirect, and combined trust values) and upload them to RSUs. Then, RSUs dynamically update the trust threshold by aggregating vehicular trust values. In the adjudication stage, RSUs punish/reward vehicles by comparing the trust threshold to aggregated trust values. In the vehicle appeal stage, vehicles appeal to other RSUs if they have received the undesired punishment by an RSU. Then, multiple RSUs jointly judge whether a vehicle is successfully appealed, and the misjudging RSU will be punished. Extensive simulations show that the proposed model effectively identifies malicious vehicles with the presence of compromised RSUs.

• Item Type: Conference Proceedings
• Additional Information: The research is supported in part by the Wuhan Key Research and Development Program (2022012202015016).
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Zhang, Professor Lei
• Authors: Wang, Y., Zhang, Y.’a., Song, Y., Cao, Y., Zhang, L., and Ren, X.
• College/School: College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
• ISSN: 1558-2612
• ISBN: 9781665491228
• Copyright Holders: Copyright © 2023, IEEE
• First Published: First published in 2023 IEEE Wireless Communications and Networking Conference (WCNC)
• Publisher Policy: Reproduced in accordance with the publisher copyright policy

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