Trustworthy VANET: Hierarchical DAG-Based Blockchain Solution With Proof of Reputation Consensus Algorithm

Dong, Z., Wu, H., Li, Z., Mi, D., Popoola, O. and Zhang, L. (2024) Trustworthy VANET: Hierarchical DAG-Based Blockchain Solution With Proof of Reputation Consensus Algorithm. In: 2023 IEEE International Conference on Blockchain (BSS2023), Danzhou, Hainan, China, 17-21 December, 2023, pp. 127-132. ISBN 9798350319293 (doi: 10.1109/Blockchain60715.2023.00030)

Abstract

The new paradigm edge computing demonstrates significant advantages in quality of service including low latency and bandwidth efficiency when deployed in autonomous vehicle applications. However, deploying edge computing in the context of a widely used vehicular ad hoc network (VANET) leads to potential security issues. Blockchain is a promising technology to solve security and trust issues with the identically distributed structure as edge computing and VANET, but its efficiency and scalability limitations constrain the usage in VANET. This paper proposes a hierarchical Directed Acyclic Graph (DAG)based blockchain architecture to overcome these integration challenges. The hierarchical architecture divides the whole system into multiple local chains according to geographical regions to improve scalability while also maintaining a global chain to facilitate security. The DAG-based blockchain structure can better support simultaneous operations to further improve scalability and efficiency. In addition, in recognition of VANET’s unique requirements, we design a reputation-based consensus for tip selection algorithm (TSA) to replace the widely used Proof-of-Work TSA in DAG, which ensures security in VANET without heavy computational burden. Our experimental simulations reveal that our proposed scheme not only fortifies security but also elevates scalability and efficiency.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Wu, Huanyu and Zhang, Professor Lei and Popoola, Dr Olaoluwa and dong, zhongxu and Li, Zongyao
• Authors: Dong, Z., Wu, H., Li, Z., Mi, D., Popoola, O., and Zhang, L.
• College/School: College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
• ISSN: 2834-9946
• ISBN: 9798350319293
• Copyright Holders: Copyright © 2023, IEEE
• First Published: First published in 2023 IEEE International Conference on Blockchain (Blockchain)
• Publisher Policy: Reproduced in accordance with the publisher copyright policy

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