Mobile crowd sensing has been a very important paradigm for collecting sensing data from a large number of mobile nodes\ndispersed over a wide area. Although it provides a powerful means for sensing data collection, mobile nodes are subject to privacy\nleakage risks since the sensing data from a mobile node may contain sensitive information about the sensor node such as physical\nlocations.Therefore, it is essential for mobile crowd sensing to have a privacy preserving scheme to protect the privacy of mobile\nnodes. A number of approaches have been proposed for preserving node privacy in mobile crowd sensing. Many of the existing\napproaches manipulate the sensing data so that attackers could not obtain the privacy-sensitive data. The main drawback of these\napproaches is that the manipulated data have a lower utility in real-world applications. In this paper, we propose an approach\ncalled
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