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Managing Trust for Intelligence Vehicles: A Cluster Consensus Approach

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Internet of Vehicles - Safe and Intelligent Mobility (IOV 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9502))

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Abstract

Managing trust is critical for Intelligence Vehicles (IVs) collaboration. Forming clusters/platoons, IVs can work together to accomplish complex jobs that they are unable to perform individually. To improve safety and efficiency of collaboration, IVs’ trust management has been extensively studied and a number of approaches have been proposed. However, most of these proposals either pay little attention on consensus forming among vehicles or ignore the utility of networked Road-Side-Units(RSUs). In this paper, we introduce a cluster consensus-based trust management scheme for IVs, where some malicious or incapable vehicles are existing on roads. The proposed scheme works by allowing IVs to evaluate each other, communicate and finally converge to a consensus where some trustworthy Cluster Head (CH) are generated. Periodically, the CHs take responsibility for intra-cluster trust management. Moreover, the scheme is enhanced with a distributed supervising mechanism and a central reputation arbitrator. The simulation results show that our scheme can achieve a high robustness to malicious/incapable IVs by limiting failure rate below 1 %.

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Acknowledgment

This work is supported by the National High-tech Research and Development Program (863) of China under Grant No. 2012AA111601, and 2015 Construction of key discipline under No. 700200253.

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Correspondence to Shu Yang .

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© 2015 Springer International Publishing Switzerland

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Yang, S., Li, J., Liu, Z., Wang, S. (2015). Managing Trust for Intelligence Vehicles: A Cluster Consensus Approach. In: Hsu, CH., Xia, F., Liu, X., Wang, S. (eds) Internet of Vehicles - Safe and Intelligent Mobility. IOV 2015. Lecture Notes in Computer Science(), vol 9502. Springer, Cham. https://doi.org/10.1007/978-3-319-27293-1_19

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  • DOI: https://doi.org/10.1007/978-3-319-27293-1_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27292-4

  • Online ISBN: 978-3-319-27293-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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