Abstract—Privacy preserving in location based queries. With the pervasiveness of location-aware mobile electronic devices and the advances of wireless communications, location-based services (LBS), which can help people enjoy a convenient life, has attracted considerable interest recently. However, < Final Year Projects > the privacy issues of LBS are still challenging today. Aiming at the challenges, in this paper, we present a new efficient and privacy-preserving LBS query scheme in outsourced cloud, i.e., EPQ, for pervasive smartphones. In the EPQ scheme, the LBS provider’s data are first outsourced to the cloud server in an encrypted manner, and then, a registered user can get accurate LBS query results without divulging his/her location information to the LBS provider and the cloud server. Specifically, based on an improved homomorphic encryption technique over a composite order group, a special spatial range query algorithm SRQC over ciphertext is proposed, with which EPQ achieves privacy preservation of user’s query and confidentiality of LBS data in the outsourced cloud server. Through detailed security analysis, we show that EPQ can resist various known security threats. In addition, we also implement EPQ over a smartphone and three workstations with a real LBS data set, and extensive simulation results further demonstrate that the proposed EPQ scheme is highly efficient at the smartphone side and can be implemented effectively in the cloud server.
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