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Article
Expressive query over outsourced encrypted data
Information Sciences
  • Yang YANG, Fuzhou University
  • Ximeng LIU, Singapore Management University
  • Robert H. DENG, Singapore Management University
Publication Type
Journal Article
Version
acceptedVersion
Publication Date
5-2018
Abstract

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.

Keywords
  • Query over encrypted data,
  • Range search,
  • Boolean search,
  • Subset search,
  • multiple users
Identifier
10.1016/j.ins.2018.02.017
Publisher
Elsevier
Copyright Owner and License
Authors
Creative Commons License
Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International
Additional URL
https://doi.org/10.1016/j.ins.2018.02.017
Citation Information
Yang YANG, Ximeng LIU and Robert H. DENG. "Expressive query over outsourced encrypted data" Information Sciences Vol. 442-443 (2018) p. 33 - 53 ISSN: 0020-0255
Available at: http://works.bepress.com/robert-deng/81/