Leveraging social networks as an underlying infrastructure for participatory sensing systems provides an effective means to have access to a reasonable number of participants, which is essential for the success of this new and exciting paradigm. Another important issue is assessing the quality of the contributions prepared by the participants, who are, on the other hand, the social network members. In this paper, we propose a trust framework for social participatory sensing systems. Our framework is aimed at quantifying the trustworthiness of contributions by considering the quality of the raw sensor readings contributed and the trustworthiness of the user contributing the sensor data, and combining them via a fuzzy inference engine to arrive at a final trust score for a contribution. It also assigns a reputation score to each user. Extensive simulations demonstrate the efficacy of our framework.

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