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
Discipline
Information Security
Research Areas
Cybersecurity
Publication
Information Sciences
Volume
442-443
First Page
33
Last Page
53
ISSN
0020-0255
Identifier
10.1016/j.ins.2018.02.017
Publisher
Elsevier
Citation
YANG, Yang; LIU, Ximeng; and DENG, Robert H..
Expressive query over outsourced encrypted data. (2018). Information Sciences. 442-443, 33-53.
Available at: https://ink.library.smu.edu.sg/sis_research/3949
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1016/j.ins.2018.02.017