Participant reputation aware data collecting mechanism for mobile crowd sensing

The malicious behaviors of participants can reduce the reliability significantly in data collecting process of Mobile Crowd Sensing. To solve this problem, a participant reputation aware data collecting mechanism is proposed, which analyzes reputation state, quantifies historical reputation of participants according to willingness and data quality, and then updates the reputation of participants by logistic regression function. Furthermore, the server can accurately choose participant and efficiently collect sensing data in multitasking scenario. Simulation results show that the proposed mechanism can significantly improve the quality of sensing data with excellent real-time performance and reduce overhead.