Cryptology ePrint Archive: Report 2017/472

A Unified Framework for Secure Search Over Encrypted Cloud Data

Cengiz Orencik and Erkay Savas and Mahmoud Alewiwi

Abstract: This paper presents a unified framework that supports different types of privacy-preserving search queries over encrypted cloud data. In the framework, users can perform any of the multi-keyword search, range search and k-nearest neighbor search operations in a privacy-preserving manner. All three types of queries are transformed into predicate-based search leveraging bucketization, locality sensitive hashing and homomorphic encryption techniques. The proposed framework is implemented using Hadoop MapReduce, and its efficiency and accuracy are evaluated using publicly available real data sets. The implementation results show that the proposed framework can effectively be used in moderate sized data sets and it is scalable for much larger data sets provided that the number of computers in the Hadoop cluster is increased. To the best of our knowledge, the proposed framework is the first privacy-preserving solution, in which three different types of search queries are effectively applied over encrypted data.

Category / Keywords: applications / encrypted cloud data, multi-keyword search, k-nearest neighbor, range search, privacy preservation, scoring

Date: received 27 May 2017

Contact author: cengizorencik at beykent edu tr

Available format(s): PDF | BibTeX Citation

Version: 20170528:185737 (All versions of this report)

Short URL: ia.cr/2017/472

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