Preserving Trajectory Privacy in Participatory Sensing Applications

With the advancement of technology in fields of wireless communication, different mobile communicating devices equipped with variety of embedded sensors and powerful sensing have been emerged. Participatory sensing is the process that enables individuals to collect, analyze and share local knowledge with their own mobile devices. Although the use of participatory sensing offers numerous benefits on deployment costs, availability, spatial- temporal coverage, energy consumption and so forth, it has certain threats which may be compromise the participators location and their trajectory data. Henceforth, to ensure the participators privacy is the most urgent task. The existing proposals emphasized more on participators location privacy and very few of them consider the privacy of the trajectories. The theoretical mix zones model are been improved by considering time factor from the viewpoint of the graph theory and mix zone graph model has been presented. Mix Zone is a area where no application can track the user. Pseudonyms are generally changed in this mix zone. The existing system has applied only a single mix zone. The privacy of the user can be further enhanced by applying Mix Zone Graph Model at multiple sensitive locations rather considering only single mix zone. So the main objective here is to apply Mix Zone Graph Model at multiple sensitive locations in order to preserve and enhance the user privacy. Further this model considers only sensitive trajectories for providing privacy thereby reducing overall storage space. The results shows that the proposed system is having better privacy level as compared to existing techniques and overall the system is time as well as space efficient.