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Bit2CV: A Novel Bitcoin Anti-Fraud Deposit Scheme for Connected Vehicles | IEEE Journals & Magazine | IEEE Xplore

Bit2CV: A Novel Bitcoin Anti-Fraud Deposit Scheme for Connected Vehicles


Abstract:

Connected vehicles (CVs) are getting increasing attention in intelligent transportation systems (ITSs). In terms of the stringent security and anonymity issues, a novel a...Show More

Abstract:

Connected vehicles (CVs) are getting increasing attention in intelligent transportation systems (ITSs). In terms of the stringent security and anonymity issues, a novel anonymous and decentralized payment platform is demanded. Bitcoin is regarded as a potential solution. But the existing Bitcoin and its various improvements lack a beforehand anti-fraud Bitcoin deposit scheme, which is necessary to prevent potential fraud risks from Bitcoin to CVs. This paper aims to build a novel anti-fraud deposit scheme as a seamless bridge between CV networks and the Bitcoin payment platform. We propose a Bitcoin-to-Connected-Vehicle deposit scheme (Bit2CV) with an outsourcing endorsement in order to build an anti-fraud deposit transaction (dtr). Firstly, Bit2CV leverages a special Bitcoin-opcode-OP_RETURN based method to record the dtr, the CV's request, and the endorsement together on Blockchain ledger. This method can achieve security features, including non-repudiation, privacy-friendly endorsement, future audit, and anti-fraud. Meanwhile, Bit2CV is fully decentralized without any involvement of centralized authorities and fully compatible with the current Bitcoin network. We conduct the security analysis and also simulations for performance evaluation. In a typical scenario of our simulation, Bit2CV total time cost is less than 477.03 ms, and the size of the endorsement is 1,732 bytes, which is much less and smaller than transaction confirmation time and the average block size, respectively. These designs and results demonstrate that Bit2CV is feasible and practical.
Published in: IEEE Transactions on Intelligent Transportation Systems ( Volume: 22, Issue: 7, July 2021)
Page(s): 4181 - 4193
Date of Publication: 10 November 2020

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