Trust and Privacy Challenges in Social Participatory Networks

Abstract

Trust and privacy in social participatory sensing systems have always been challenging issues. Trust and privacy are somehow interconnected and interdependent concepts, and solutions that take into account both of these two parameters simultaneously will result in better people evaluation in the context of social participatory networks. In this paper, we propose a trust and privacy aware framework for recruiting workers in social participatory networks which controls and adjusts the privacy and trustworthiness of workers accordingly. The proposed method employs the reputation scores gained by a worker to adjust the privacy settings from which the worker can benefit. This interdependency helps requesters find more suitable workers. The simulation results show the promising behavior of the proposed framework.