PROJECT TITLE :

Privacy and Quality Preserving Multimedia Data Aggregation for Participatory Sensing Systems

ABSTRACT:

With the recognition of mobile wireless devices equipped with various sorts of sensing abilities, a new service paradigm named participatory sensing has emerged to provide users with brand new life expertise. But, the wide application of participatory sensing has its own challenges, among which privacy and multimedia data quality preservations are 2 critical issues. Unfortunately, none of the existing work has totally solved the problem of privacy and quality preserving participatory sensing with multimedia knowledge. During this paper, we tend to propose SLICER , which is the primary -anonymous privacy preserving theme for participatory sensing with multimedia information. SLICER integrates a data coding technique and message transfer methods, to achieve sturdy protection of participants’ privacy, while maintaining high knowledge quality. Specifically, we study two sorts of information transfer methods, particularly transfer on join up (TMU) and minimal price transfer (MCT). For MCT, we tend to propose two totally different but complimentary algorithms, including an approximation algorithm and a heuristic algorithm, subject to completely different strengths of the necessity. Furthermore, we have implemented SLICER and evaluated its performance using publicly released taxi traces. Our analysis results show that SLICER achieves high information quality, with low computation and communication overhead.