TECS: A Trust Model for VANETs Using Eigenvector Centrality and Social Metrics

Zhang, Yu’Ang; Song, Yujie; Wang, Yu; Cao, Yue; Ren, Xuefeng; Yan, Fengping

doi:10.1109/trustcom56396.2022.00016

2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) 2022

DOI: 10.1109/trustcom56396.2022.00016

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TECS: A Trust Model for VANETs Using Eigenvector Centrality and Social Metrics

Yu’Ang Zhang

Yujie Song

Yu Wang

et al.

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2024

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Multidimensional Trust Evidence Fusion and Path-Backtracking Mechanism for Trust Management in VANETs

Cheong,

Song,

Cao

et al. 2024

IEEE Internet Things J.

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With the development of Vehicular Ad-hoc Networks (VANETs), several data security challenges are revealed, such as data hijacking and interception. Although vehicles are authorized, malicious behaviors still be carried out. Security lapses may lead to potential accidents, which emphasizes the importance of laying a solid security foundation for VANETs. Thanks to the base security layer provided by cryptography technologies, security problems can be solved in VANETs to avoid accidents. However, trust management focuses on the analysis and identification of misbehavior, to ensure secure interactions among vehicles, and preserve data integrity against security issues. This paper explores trust assessments that consider the transmission path of message as a novel indicator, to provide a comprehensive and accurate trust assessment. We propose a Multidimensional trust Evidence Fusion and Path-Backtracking mechanism for trust management scheme (MEFPB) in VANETs. MEFPB integrates the multidimensional trust evidence fusion and path-backtracking mechanism. Specifically, MEFPB utilizes the Dempster-Shafer theory to fuse multi-dimensional indicators (direct trust, indirect trust, and transmission path of message) for evaluating the trustworthiness of vehicles. The direct and indirect trust are supplied by the message-sending vehicle and its neighbors (i.e., other vehicles). The transmission path of message is provided by roadside units. Furthermore, the path-backtracking mechanism identifies and traces malicious behaviors based on the transmission path of message. Moreover, extensive experiments demonstrate that our scheme significantly outperforms other baseline schemes, exhibiting a high malicious behavior detection rate within VANETs.

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Multidimensional Trust Evidence Fusion and Path-Backtracking Mechanism for Trust Management in VANETs

Cheong,

Song,

Cao

et al. 2024

IEEE Internet Things J.

Self Cite

View full text Add to dashboard Cite

show abstract

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TECS: A Trust Model for VANETs Using Eigenvector Centrality and Social Metrics

Cited by 1 publication

References 27 publications

Multidimensional Trust Evidence Fusion and Path-Backtracking Mechanism for Trust Management in VANETs

Multidimensional Trust Evidence Fusion and Path-Backtracking Mechanism for Trust Management in VANETs

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