Abstract
In participatory sensing, participants contribute sensing data to task center. However, the task center is not always trustworthy. It may try to profile the participants by data mining, which is a great threat to the privacy of participants. To solve this problem, three collaborative data exchange strategies are studied. Participants exchange sensing data before upload to the task center. The mixed data protect the participants’ privacy from data mining by the task center. The simulations show that the unequal data exchange strategy is more efficient than the full exchange strategy because it considers both the tradeoff between privacy preservation and the cost of data exchange.
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