Trajectory Privacy in Participatory Sensing using K-anonymity

Development of mobile communication, applications represents a challenge for both conceptually and technically so the basic requirements of LBS (location-based services) are numerous. Complex task is to provide user with added value to location information. Previously using Trajectory privacy-preserving framework user’s location is preserved using various techniques, but the locations of users trajectories may not sensitive all the time. Even mix-zones are regions where users movement cannot be track by any applications. In this paper mobile users will reveal their location to database services in a periodic or on-demand manner. K-anonymity preserving management of location information by developing efficient and scalable system-level facilities for protecting the location privacy through ensuring location k-anonymity. In the context of LBSs and mobile clients, location k-anonymity refers to the k-anonymity usage of location information. A subject is considered location k-anonymous if and only if the location information sent from a mobile client to an LBS is indistinguishable from the location information of at least k -1 other mobile clients. New spatial cloaking techniques based on real or historical user trajectory is designed to protect user location trajectories and also satisfy the users’ specified k-anonymity level.