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A Vehicular Trust Blockchain Framework with Scalable Byzantine Consensus

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journal contribution
posted on 2024-02-22, 14:16 authored by Xiao Chen, Guoliang Xue, Ruozhou Yu, Haiqin Wu, Dawei Wang

The maturing blockchain technology has gradually promoted decentralized data storage from cryptocurrencies to other applications, such as trust management, resulting in new challenges based on specific scenarios. Taking the mobile trust blockchain within a vehicular network as an example, many users require the system to process massive traffic information for accurate trust assessment, preserve data reliably, and respond quickly. While existing vehicular blockchain systems ensure immutability, transparency, and traceability, they are limited in terms of scalability, performance, and security. To address these issues, this paper proposes a novel decentralized vehicle trust management solution and a well-matched blockchain framework that provides both security and performance. The paper primarily addresses two issues: i) To provide accurate trust evaluation, the trust model adopts a decentralized and peer-review-based trust computation method secured by trusted execution environments (TEEs). ii) To ensure reliable trust management, a multi-shard blockchain framework is developed with a novel hierarchical Byzantine consensus protocol, improving efficiency and security while providing high scalability and performance. The proposed scheme combines the decentralized trust model with a multi-shard blockchain, preserving trust information through a hierarchical consensus protocol. Finally, real-world experiments are conducted by developing a testbed deployed on both local and cloud servers for performance measurements.

History

Author affiliation

College of Science & Engineering/Comp' & Math' Sciences

Version

  • AM (Accepted Manuscript)

Published in

IEEE Transactions on Mobile Computing

Pagination

1 - 13

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

issn

1536-1233

eissn

1558-0660

Copyright date

2023

Available date

2024-02-22

Language

en

Deposited by

Dr Xiao Chen

Deposit date

2024-02-12

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