Published Paper Details:

Recent advances in positioning techniques, small devices, GIS-based services, and ubiquitous connectivity, have enabled a large variety of location-based services able to tailor services according to the location of the individual requiring the service. Location information, however, if on one side is critical for providing customized services, on the other hand, if misused, can lead to privacy breaches. Location Privacy is the serious issue where the location can be easily traced with the given system. In images there will be metadata where it contains all the image details in at. At first the feature extraction will be made using Recurrent Neural Network (RNN) thus the location feature are get known. A dummy location is done with the Pseudo random Function and the metadata location is changed. The user can access only when the access is provided to them. Here the user access can be provided by the authority who they wish to share their location. Our scheme employs an entity, termed Function Generator, to distribute the spatial transformation parameters periodically, with which the users and the LSP(location service provider) can performs the mutual transformation between a real location and a pseudo location. Without the transforming parameters, the anonymizer cannot have any knowledge about a user�s real location. The main merits of our scheme include (1) no fully trusted entities are required; (2) each user can obtain accurate POIs, while preserving location privacy.