research-article

Expressive query over outsourced encrypted data

Authors:

Robert DengAuthors Info & Claims

Information Sciences—Informatics and Computer Science, Intelligent Systems, Applications: An International Journal, Volume 442, Issue C

Pages 33 - 53

https://doi.org/10.1016/j.ins.2018.02.017

Published: 01 May 2018 Publication History

Abstract

This system supports expressive search query patterns: single/conjunctive keyword queries, equality, multi-dimensional range queries, subset queries and Boolean queries.Keyword weight and preference score are set for the keyword index and query trapdoor, respectively. The cloud server computes the relevance scores in an encrypted form and returns the top-k results to data user.The system enables the data owner to define authorization period to control the user authorization and revocation.The system enables a data user to use a single query trapdoor to search over encrypted documents from multiple data owners.The search result in this system is in ciphertext form and only the authorized data user is able to decrypt the result, which prevents the off-line KG attack. Data security and privacy concerns in cloud storage services compel data owners to encrypt their sensitive data before outsourcing. Standard encryption systems, however, hinder users from issuing search queries on encrypted data. Though various systems for search over encrypted data have been proposed in the literature, existing systems use different encrypted index structures to conduct search on different search query patterns and hence are not compatible with each other. In this paper, we propose a query over encrypted data system which supports expressive search query patterns, such as single/conjunctive keyword query, range query, boolean query and mixed boolean query, all using a single encrypted index structure. To the best of our knowledge, the proposed system enables the most expressive query pattern search among all the existing solutions. In addition, the system allows data users to simultaneously query over encrypted documents from multiple data owners using one query trapdoor and supports flexible user authorization and revocation. We show that our system is secure and resists keyword guessing attack. We also conduct extensive experiments and demonstrate that the system is more efficient than other public key searchable encryption systems.

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Cited By

Liu XYang GSusilo WHe KDeng RWeng J(2023)Privacy-Preserving Multi-User Outsourced Computation for Boolean CircuitsIEEE Transactions on Information Forensics and Security10.1109/TIFS.2023.330173418(4929-4943)Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1109/TIFS.2023.3301734
Zhang YYou LLi Y(2021)Tree-Based Public Key Encryption with Conjunctive Keyword SearchSecurity and Communication Networks10.1155/2021/70349442021Online publication date: 5-Nov-2021
https://dl.acm.org/doi/10.1155/2021/7034944
Ying ZZhang YCao SXu SMa M(2021)OIDPRTransactions on Emerging Telecommunications Technologies10.1002/ett.395332:5Online publication date: 7-May-2021
https://dl.acm.org/doi/10.1002/ett.3953
Show More Cited By

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cover image Information Sciences: an International Journal

Information Sciences: an International Journal Volume 442, Issue C

May 2018

235 pages

ISSN:0020-0255

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Copyright © Elsevier Inc.

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Elsevier Science Inc.

United States

Publication History

Published: 01 May 2018

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Cited By

Liu XYang GSusilo WHe KDeng RWeng J(2023)Privacy-Preserving Multi-User Outsourced Computation for Boolean CircuitsIEEE Transactions on Information Forensics and Security10.1109/TIFS.2023.330173418(4929-4943)Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1109/TIFS.2023.3301734
Zhang YYou LLi Y(2021)Tree-Based Public Key Encryption with Conjunctive Keyword SearchSecurity and Communication Networks10.1155/2021/70349442021Online publication date: 5-Nov-2021
https://dl.acm.org/doi/10.1155/2021/7034944
Ying ZZhang YCao SXu SMa M(2021)OIDPRTransactions on Emerging Telecommunications Technologies10.1002/ett.395332:5Online publication date: 7-May-2021
https://dl.acm.org/doi/10.1002/ett.3953
Zhang CZhu LXu CSharif KZhang CLiu X(2020)PGASInformation Sciences: an International Journal10.1016/j.ins.2019.07.082506:C(325-345)Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.1016/j.ins.2019.07.082

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