$\mathcal {R}$-Manager: Consortium Blockchain-Based Vehicle Reputation Management for High-Quality Reports in Traffic-Oriented Crowdsourcing

Abstract

The rise of 5G communication technology brings opportunities to traffic-oriented crowdsourcing in the Internet of Vehicles (IoV). As vehicles act as workers in many traffic-oriented crowdsourcing systems, there's a growing focus on how to get high-quality reports when some vehicles may be malicious or selfish. Some researchers assign reputation values to vehicles and select high-reputation vehicles to complete tasks, but these efforts still have shortcomings. In model design, guaranteeing the objectivity of reputation calculation, suppressing malicious and selfish behaviors, and maximizing the utilities of honest vehicles and service providers should be considered simultaneously. In system construction, reputation verification service in multi-party intelligent transportation scenarios and reputation management system performance should be satisfied. In this paper, we propose $\mathcal {R}$-manager, a consortium blockchain-based vehicle reputation management scheme. Firstly, we design a reputation model that uses confirmed results to update reputation and suppress malicious and selfish behaviors based on reputation deposit forfeit and a tax mechanism. Besides, the model maximizes the utilities of crowdsourcing participants by reaching the game equilibrium. Secondly, we design a reputation management system based on a consortium blockchain to abstract management activities as transactions and verify them by executing smart contracts, which meet multi-party management and reputation verification needs. Moreover, we design a half-committee endorsement strategy to improve system performance. Finally, our model is verified by simulation, and it can better suppress malicious and selfish behaviors compared with three different reputation models. We implement a prototype system and evaluate its performance. $\mathcal {R}$-manager outperforms two state-of-the-art blockchain-based schemes.