EPLQ: Efficient Privacy-Preserving Location-based Query over Outsourced Encrypted Data
ABSTRACT
The pervasiveness of smart phones, location based 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 privacy preserving 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, wefurther 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 privacy preserving 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.
1Existing Solution:
Exist system has no location based query.
There is no security level and chance to hack someone data.
2.2 Proposed Solution:
The use of LBSalso 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.
Software Requirements:
Front End: HTML5, CSS3, JS, BootStrap
BackEnd: PHP, MYSQL
Control End: Angular JS