An Efficient Location Privacy Preserving Model based on Geohash With the rapid development of locationaware mobile devices, locationbased services have been widely used. When LBS (Location Based Services) bringing great convenience and profits, it also brings great hidden trouble, among which user privacy security is one of them. The paper builds a LBS privacy protection model and develops algorithm depend on the technology of one dimensional coding of Geohash geographic information. The results of experiments and data measurements show that the model the model has reached kanonymity effect and has good performance in avoiding attacking from the leaked information in a continuous query with the useru0027s background knowledge. It also has a preferable performance in time cost of system process.

An Approach Based on Customized Robust Cloaked Region for Geographic Location Information Privacy Protection Locationbased services (LBS) have gained huge popularity because of the easy availability of modern mobile devices and the fast development of geographical information science (GIS). However, the lack of protection for private user positions might give rise to privacy concerns. This kind of problem is especially serious in mobile application environment because many mobile applications tend to use LBS. In this paper, we propose a new privacy preserving approach using customized robust cloaked region (RCR), depending on a peertopeer structure and the premise that users do not trust each other when sharing their geographical locations. Two algorithms are used to generate the RCR with high user density. The area of the RCR is controlled by the userxe2x80x99s demanded degree of protection. To enhance the resistance to regional background knowledge attack, we incorporate a location semantic value into each unit of the user map. According to extensive simulations, our method can effectively obfuscate a userxe2x80x99s geographical location into a highly indistinguishable region because of the disturbance of nearby users and different equally possible locations.