K-Anonymous Privacy Preserving Technique for Participatory Sensing With Multimedia Data Over Cloud Computing
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Abstract
Nowadays, there are distinctions of sensing facilities equipped with mobile wireless devices. Likewise, a different service provider named participatory sensing system is made available, which gives outstanding life experience to users. Nevertheless, there are many challenges like privacy and multimedia data quality. There is no any earlier system that can resolve problems of confidentiality and quality, preserving participatory sensing system with multimedia data. Slicer is a K-anonymous privacy preservation scheme for participatory sensing with multimedia data over the cloud framework. It combines data coding methods and message transfer strategies to get the secure protection of user's high data quality and also maintains privacy. Two data transfer strategies are used, namely Minimal Cost Transfer and Transfer On Meet-up. For Minimal Cost Transfer, two parallel algorithms are used, i.e., approximation algorithm and Heuristic algorithm. Slicer provides data quality with low communication.
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