TI-BIoV: Traffic Information Interaction for Blockchain-Based IoV With Trust and Incentive

Recent Blockchain-based Internet of Vehicles (BIoV) solutions are proposed to provide the capabilities of trust management and incentive distribution for traffic information interaction in decentralized trustless Internet of Vehicles (IoV). However, existing trust management methods in BIoV are designed based on subjective user feedback, which is vulnerable to bad-mouthing and collusion attacks. Besides, these incentive strategies achieve accurate information interaction based on the game theory, yet it is challenging for the practical IoV scenario without completely explicit parameters. To address these issues, we propose TI-BIoV, a traffic information interaction system based on three blockchains for IoV with the nonsubjective trust evaluation and optimal incentive with partial inexplicit parameters. Specifically, a nonsubjective trust mechanism is designed based on the traffic information offset calculated by other related traffic information, which ensures the change of vehicle trust value without any subjective factors. On this basis, a trust-based consensus protocol, which selects entities with high trust values as participants, is given to realize the reliable public audit of transactions. According to traffic information accuracy measurements, we develop a
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-learning-based algorithm to encourage vehicles continuously submit accurate traffic information and optimally schedule the incentive for both platform and vehicle via training with incompletely explicit parameters of TI-BIoV. Finally, we analyze the security properties and common attacks of TI-BIoV and implement a prototype. The experimental results show that TI-BIoV achieves reliable consensus with nonsubjective trust evaluation and runs stably for a long time with two-sided incentive strategies.