Spatial Crowdsourcing (SC) is a emerging outsourcing platform that allocates spatio-temporal tasks to a set of workers. However, it usually demands workers to upload their privacy information to untrustworthy entities, which causes a privacy breach. In this paper, we consider a complex SC scenario, in which each worker has a skill, whereas each spatial task requires a set of skills. Under this scenario, we propose a novel framework that can protect the location and skill privacy of workers while providing effective task assignment. Experimental results on both real and synthetic data sets show the effectiveness and efficiency of our proposed framework.
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