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Towards Efficient Privacy-Preserving Truth Discovery in Crowd Sensing Systems

With the rapid development of portable mobile devices, crowd sensing systems have been recognized as a key technology to utilize the data collected by the portable mobile devices towards scalable and flexible mobile services. However, since the information provided by devices may not be reliable, the aggregated results of the collected data may not be accurate. To tackle this challenge, various truth discovery schemes have been proposed. On the other hand, a practical issue of privacy protection is not considered in most existing truth discovery schemes. In this paper, we propose an Efficient Privacy-preserving Truth Discovery (EPTD) in Crowd Sensing Systems, which can protect the privacy of users' observed values and weights in truth discovery process. Finally, we show the performance of our scheme is better than existing models in terms of computation overhead.