Best project center chennaiWith the pervasiveness of smart phones, locationbased services (LBS) have received considerable attention and become more popular and vital recently. However, the use of LBS also poses a potential threat to user’s location privacy. In this paper, aiming at spatial range query, a popular LBS providing information about POIs (Points Of Interest) within a given distance, we present an efficient and privacy-preserving location based query solution, called EPLQ. Specifically, to achieve privacypreserving spatial range query, we propose the first predicateonly encryption scheme for inner product range, which can be used to detect whether a position is within a given circular area in a privacy-preserving way. To reduce query latency, we further design a privacy-preserving tree index structure in EPLQ. Detailed security analysis confirms the security properties of EPLQ. In addition, extensive experiments are conducted, and the results demonstrate that EPLQ is very efficient in privacypreserving spatial range query over outsourced encrypted data. In particular, for a mobile LBS user using an Android phone, around 0.9 second is needed to generate a query; and it also only requires a commodity workstation, which plays the role of the cloud in our experiments, a few seconds to search POIs.Best project center chennai | Best project center chennai
With the pervasiveness of smart phones, locationbased services (LBS) have received considerable attention and become more popular and vital recently. However, the use of LBS also poses a potential threat to user’s location privacy. In this paper, aiming at spatial range query, a popular LBS providing information about POIs (Points Of Interest) within a given distance, we present an efficient and privacy-preserving location based query solution, called EPLQ. Specifically, to achieve privacypreserving spatial range query, we propose the first predicateonly encryption scheme for inner product range, which can be used to detect whether a position is within a given circular area in a privacy-preserving way. To reduce query latency, we further design a privacy-preserving tree index structure in EPLQ. Detailed security analysis confirms the security properties of EPLQ. In addition, extensive experiments are conducted, and the results demonstrate that EPLQ is very efficient in privacypreserving spatial range query over outsourced encrypted data. In particular, for a mobile LBS user using an Android phone, around 0.9 second is needed to generate a query; and it also only requires a commodity workstation, which plays the role of the cloud in our experiments, a few seconds to search POIs.