Research On Privacy-Preserving Incentive Mechanism In Vehicular Crowdsensing

Vehicular crowdsensing uses vehicles to sense the environment,collect data and provide information services,and it plays an important role in the construction of intelligent transportation and smart city.The incentive mechanism acts as an effective solution to improve the participation and completion quality of sensing tasks and has become an important direction in the research of vehicular crowdsensing.Most of the existing incentive mechanisms in the Internet of vehicles are based on the trusted third party,which has the disadvantages of single point of failure and being prone to collusion attacks.The participation of trusted party can also lead to the privacy disclosure at different stages of the sensing task,such as identity authentication,reputation update,or reward distribution.Although the existing distributed incentive mechanism partially solves the problem of single point of failure and collusion attack,there still exists some shortcomings in terms of privacy preservation.The shortcomings refer to requiring the participation of a third party and high consumption in privacypreserving schemes and cannot resist Sybil attacks,etc.In addition,the fairness of reward calculation and reputation update is also a key role in the incentive mechanism.In some existing incentive mechanisms,dishonest vehicles can also get rewards and their reputation will not be reduced even they submit low-quality data.Because they do not consider the quantification of data quality or only consider single influencing factor to calculate data quality.This will reduce the willingness of honest vehicles to participate in sensing tasks and damage the utility of task initiators.Therefore,this paper studies the privacy leakage and fairness problems of the incentive mechanism in vehicular crowdsensing.This paper proposes a privacy-preserving distributed incentive mechanism and fair reputation management scheme in the vehicular crowdsensing scenario,based on blockchain and smart contracts,auction theory,rating feedback mechanism,and cryptography technology.The proposed incentive mechanism completes the incentive algorithm by invoking the smart contract which solves the security problem in centralized systems.Protecting the vehicles’ identity privacy and bid privacy by leveraging zero-knowledge-based anonymous certificate algorithm and Pedersen commitments scheme respectively.Ensuring the fairness of reward calculation by quantifying data quality based on data accuracy and timeliness.The proposed fair reputation management scheme realizes privacy protection for honest vehicles and punishment for misbehaved vehicles based on the traceable ring signature algorithm.Then the fairness of reputation calculation is ensured by data quality quantification algorithm which is based on the data truthfulness and timeliness.In addition,the ZeroKnowledge Succinct Non-Interactive Argument of Knowledge zk-SNARK scheme is used to realize the anonymous and legal reputation updating of vehicles.Security analysis and experimental results show that the proposed incentive mechanism and reputation management scheme are feasible and effective.