Scinovex
articleTop 1% cited

Blockchain-Based Decentralized Trust Management in Vehicular Networks

IEEE Internet of Things Journal · 2018 · Vol. 6(2) · pp. 1495–1505
Zhe YangKan YangLei LeiKan ZhengVictor C. M. Leung

Abstract

Vehicular networks enable vehicles to generate and broadcast messages in order to improve traffic safety and efficiency. However, due to the nontrusted environments, it is difficult for vehicles to evaluate the credibilities of received messages. In this paper, we propose a decentralized trust management system in vehicular networks based on blockchain techniques. In this system, vehicles can validate the received messages from neighboring vehicles using Bayesian Inference Model. Based on the validation result, the vehicle will generate a rating for each message source vehicle. With the ratings uploaded from vehicles, roadside units (RSUs) calculate the trust value offsets of involved vehicles and pack these data into a “block.” Then, each RSU will try to add their “blocks” to the trust blockchain which is maintained by all the RSUs. By employing the joint proof-of-work (PoW) and proof-of-stake consensus mechanism, the more total value of offsets (stake) is in the block, the easier RSU can find the nonce for the hash function (PoW). In this way, all RSUs collaboratively maintain an updated, reliable, and consistent trust blockchain. Simulation results reveal that the proposed system is effective and feasible in collecting, calculating, and storing trust values in vehicular networks.

Blockchain Technology Applications and SecurityVehicular Ad Hoc Networks (VANETs)Privacy-Preserving Technologies in DataBlockchainComputer scienceTrust management (information system)Computer networkComputer securityDistributed computing

Funding

  • National Natural Science Foundation of China
  • Beijing University of Posts and Telecommunications
Citations
911
FWCI
182.40
field-weighted impact
References
29
Percentile
100%
vs. same field & year
Citations per year
Cited by
References
Citation Network

How this paper connects to the literature. Drag to explore, click any node to open that paper.