A Hybrid Approach to Trust Node Assessment and Management for VANETs Cooperative Data Communication: Historical Interaction Perspective

Vehicular ad hoc networks (VANETs) provide self-organized wireless multihop transmission, where nodes cooperate with each other to support data communication. However, malicious nodes may intercept or discard data packets, which might interfere with the transmission process and cause privacy leakage...

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Bibliographic Details
Published in:IEEE transactions on intelligent transportation systems 2022-09, Vol.23 (9), p.16504-16513
Main Authors: Gao, Honghao, Liu, Can, Yin, Yuyu, Xu, Yueshen, Li, Yu
Format: Article
Language:English
Subjects:
Analytical models
Bayes methods
Bayesian analysis
bayesian inference
Communication
cooperative data communication
Data communication
historical interaction records
malicious nodes
Mobile ad hoc networks
Nodes
Peer-to-peer computing
Security
Statistical inference
trust assessment and management
Trust management
Vehicular ad hoc networks
Wireless communication
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Summary:Vehicular ad hoc networks (VANETs) provide self-organized wireless multihop transmission, where nodes cooperate with each other to support data communication. However, malicious nodes may intercept or discard data packets, which might interfere with the transmission process and cause privacy leakage. We consider historical interaction data of nodes as an important factor of trust. Thus, this paper focuses on the trust node management of VANETs, which aims to quantify node credibility as an assessment method and avoid assigning malicious nodes. First, the integrated trust of each node is proposed, which consists of the direct trust and the recommended trust. The former is dynamically computed by historical interaction records and Bayesian inference considering penalty factors. The latter defines trust by third-party nodes and their reputation. Second, the process of trust calculation and data communication calls for timeliness. Therefore, we introduce a time sliding window and time decay function to ensure that the latest interaction information has a higher weight. We can sensitively identify malicious nodes and make quick responses. Finally, the experimental results demonstrate that our proposed method outperforms bassline methods, especially with respect to the packet delivery ratio and security.
ISSN:1524-9050
1558-0016
DOI:10.1109/TITS.2021.3129458