Location Privacy Preservation Scheme Based Incentive for Crowd-Sensing Networks

Abstract

Mobile crowd sensing (MCS) takes advantage of pervasive smart phones equipped with multi-sensors to collect sensing data from social events and phenomena for conducting complex sensing tasks. To achieve high quality of sensing service, on one hand, it is inevitable for mobile user to share the privacy information (e.g., identification, location, interest, etc.) with other mobile users. On the other hand, the willingness for mobile user to complete sensing task is low without incentive. Therefore, the privacy preservation and incentive scheme become critical issues that need to be considered. In this paper, a privacy preservation scheme based on differential privacy method is firstly proposed to protect the location privacy of mobile users. Secondly, the selected mobile users act as the task responders to complete sensing tasks. After that, the interaction behavior between mobile requester and mobile users is modelled as the reverse auction game, where the optimal bidding strategy is obtained by analyzing the optimization problem to stimulate mobile users to join in crowd sensing. Finally, simulation results have been conducted to validate the efficiency and effectiveness of the proposed scheme.