A Trusted Measurement Scheme for Connected Vehicles Based on Trust Classification and Trust Reverse

Zipeng Diao, Mengxiang Wang, Qiang Fu (), Bei Gong and Meng Chen
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Zipeng Diao: China National Institute of Standardization, Beijing 100191, China
Mengxiang Wang: China National Institute of Standardization, Beijing 100191, China
Qiang Fu: China National Institute of Standardization, Beijing 100191, China
Bei Gong: College of Computer Science, Beijing University of Technology, Beijing 100124, China
Meng Chen: China National Institute of Standardization, Beijing 100191, China

Mathematics, 2025, vol. 13, issue 9, 1-18

Abstract: As security issues in vehicular networks continue to intensify, ensuring the trustworthiness of message exchanges among vehicles, infrastructure, and cloud platforms has become increasingly critical. Although trust authentication serves as a fundamental solution to this challenge, existing models fail to effectively address the specific requirements of vehicular networks, particularly in defending against malicious evaluations. This paper proposes a novel multidimensional trust evaluation framework that integrates both static and dynamic metrics. To tackle the issue of malicious ratings in peer assessments, a rating reversal mechanism based on K-means clustering is designed to effectively identify and correct abnormal trust feedback. In addition, the framework incorporates an entropy-based trust weight allocation mechanism and a time decay model to enhance adaptability in dynamic environments. The simulation results demonstrate that, compared with traditional approaches, the proposed scheme improves the average successful information rate by 12% and reduces the false positive rate to 6.1%, confirming its superior performance in securing communications within the vehicular network ecosystem.

Keywords: connected vehicles; information security; trusted attestation; trust reverse (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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