A Secure and Privacy-Preserving Incentive Framework for Vehicular Cloud on the Road

Vehicular cloud, which is constituted by gathering the under-utilized on-board capabilities on the road, has received considerable attention in recent years. In this paper, we propose a novel secure and privacy-preserving incentive mechanism in vehicular cloud, which employs the Stackelberg Game to model the interaction between the leader and follower vehicles. With the proposed incentive mechanism, the leader vehicle which represents the task announcement server can select competent follower vehicles to collaborate for the announced task, and the selected follower vehicles can earn payments from participating in and completing the announced tasks. By exploiting the group signature technique, the leader and follower vehicles can achieve mutual verification with each other without privacy-related information disclosure. To show the efficiency of the proposed scheme, numerical analysis are conducted, and the derived results demonstrate that the proposed incentive mechanism can bring benefits to both parties, in terms of the utilities of the involved vehicles.