TY  - EJOU
AU  - Wang, Wenming 
AU  - Liu, Zhiquan 
AU  - Zhang, Shumin 
AU  - Liu, Guijiang 

TI  - Trust Score-Based Malicious Vehicle Detection Scheme in Vehicular Network Environments
T2  - Computers, Materials \& Continua

PY  - 2024
VL  - 81
IS  - 2
SN  - 1546-2226

AB  - Advancements in the vehicular network technology enable real-time interconnection, data sharing, and intelligent cooperative driving among vehicles. However, malicious vehicles providing illegal and incorrect information can compromise the interests of vehicle users. Trust mechanisms serve as an effective solution to this issue. In recent years, many researchers have incorporated blockchain technology to manage and incentivize vehicle nodes, incurring significant overhead and storage requirements due to the frequent ingress and egress of vehicles within the area. In this paper, we propose a distributed vehicular network scheme based on trust scores. Specifically, the designed architecture partitions multiple vehicle regions into clusters. Then, cloud supervision systems (CSSs) verify the accuracy of the information transmitted by vehicles. Additionally, the trust scores for vehicles are calculated to reward or penalize them based on the trust evaluation model. Our proposed scheme demonstrates good scalability and effectively addresses the main cause of malicious information distribution among vehicles. Both theoretical and experimental analysis show that our scheme outperforms the compared schemes.
KW  - Distributed; trust mechanism; vehicular network; privacy protection

DO  - 10.32604/cmc.2024.055184