UGC Approved Journal no 63975(19)
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ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 5 Issue 12
December-2018
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR1812598


Registration ID:
193243

Page Number

660-665

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Title

PRIVACY PRESERVING SPATIAL RANGE QUERY OVER OUTSOURCED ENCRYPTED DATA

Abstract

The 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 predicate only 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. Significant challenges still remain in the design of privacy preserving LBS, and new challenges arise particularly due to data outsourcing. In recent years, there is a growing trend of outsourcing data including LBS data because of its financial and operational benefits. Lying at the intersection of mobile computing and cloud computing, designing privacy-preserving outsourced spatial range query faces the challenges. The techniques used to realize privacy-preserving query usually increase the search latency. A novel predicate-only encryption scheme for inner product range named IPRE, which allows testing whether the inner product of two vectors is within a given range without disclosing the vectors and an efficient solution for privacy-preserving spatial range query. In particular, we show that whether a POI matches aspatial range query or not can be tested by examining whether the inner product of two vectors is in a given range. This can be used for more kinds of privacy-preserving queries over outsourced data. In the spatial range query discussed in this work, we consider Euclidean distance, which is widely used in spatial databases.

Key Words

PRIVACY PRESERVING SPATIAL RANGE QUERY OVER OUTSOURCED ENCRYPTED DATA

Cite This Article

"PRIVACY PRESERVING SPATIAL RANGE QUERY OVER OUTSOURCED ENCRYPTED DATA", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 12, page no.660-665, December-2018, Available :http://www.jetir.org/papers/JETIR1812598.pdf

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2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"PRIVACY PRESERVING SPATIAL RANGE QUERY OVER OUTSOURCED ENCRYPTED DATA", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 12, page no. pp660-665, December-2018, Available at : http://www.jetir.org/papers/JETIR1812598.pdf

Publication Details

Published Paper ID: JETIR1812598
Registration ID: 193243
Published In: Volume 5 | Issue 12 | Year December-2018
DOI (Digital Object Identifier):
Page No: 660-665
Country: -, -, - .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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