EPLQ Efficient Privacy-Preserving Location-based Query over Outsourced Encrypted Data - 2016

PROJECT TITLE:

EPLQ Efficient Privacy-Preserving Location-based Query over Outsourced Encrypted Data - 2016

ABSTRACT:

With the pervasiveness of smart phones, location-primarily based services (LBS) have received considerable attention and become additional standard and vital recently. However, the employment of LBS also poses a potential threat to user's location privacy. During this paper, aiming at spatial vary query, a common LBS providing information about points of interest (POIs) at intervals a given distance, we gift an efficient and privacy-preserving location-based query answer, called EPLQ. Specifically, to realize privacy-preserving spatial vary query, we tend to propose the first predicate-solely encryption theme for inner product range (IPRE), which will be used to detect whether or not an edge is inside a given circular space in a very privacy-preserving way. To cut back question latency, we tend to additional design a privacy-preserving tree index structure in EPLQ. Detailed security analysis confirms the protection properties of EPLQ. Moreover, in depth experiments are conducted, and also the results demonstrate that EPLQ is terribly economical in privacy-preserving spatial vary question over outsourced encrypted knowledge. In explicit, for a mobile LBS user using an Android phone, around zero.9 s is required to get a query, and it conjointly only requires a commodity workstation, that plays the role of the cloud in our experiments, some seconds to look POIs.

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