Usage of locational data is getting more popular day by day. Location-aware application, context aware application and Ubiquities applications are some of the major categories of applications which are based on locational data. One of the most concerning issues regarding such applications is how to protect user’s privacy against malicious attackers. Failing in this task would result in a total failure for the project, considering how privacy concerns are getting more and more important for the end users. In this project, we will propose a theoretical solution for protecting user privacy in location-based application against inference attacks. Our solution is based on categorizing target users into pre-defined groups (a. k. a. Personas) and utilizing their common characteristics in order to synthesize access control rules for the collected data.

Mobile applications may employ the GPS as user input to create location-based games. The existing landscape of location-based applications predominantly falls into two categories: those offering high-paced action with free movement and those providing movement between established locations at a leisurely pace. However, the combination of fast player movement between game-selected locations can potentially lead to significant accidents if the locations are poorly chosen. A naively designed system may encourage players to traverse rivers, cross highways,or trespass into private areas. This report introduces a design aimed at establishing a safe real-world environment in mobile applications by mapping the surroundings and guiding the player safely. A map generationsystem is proposed, along with a conceptual framework for utilization the generated map.