Location Privacy and Safety Recommendations in GSN

Online Social Networks have become a rich source of information wherein users of all ages readily provide their personal information. Using various GeoSocial applications, millions of people interact with their surroundings through their friends and their recommendations, without adequate privacy protection, these systems can be easily misused. Applications like targeted advertisement, personalized recommendations can be provided by the GeoSocial network with the help of the personal information aggregated by the user?s visit at a venue. This may lead the user towards a significant risk, if their personal information is somehow leaked or sold. In this paper we provide novel approach of building LCPs of current users in a secured way and also proving its location correctness where users can modify LCPs in a predefined manner only. This paper securely and privately extract, model and embed public safety information into user experiences.