Search pattern leakage in searchable encryption: Attacks and new construction

C Liu; L Zhu; Mingzhong Wang; Y A Tan

doi:10.1016/j.ins.2013.11.021

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Search pattern leakage in searchable encryption: Attacks and new construction

Journal article

Open access

Peer reviewed

Search pattern leakage in searchable encryption: Attacks and new construction

C Liu, L Zhu, Mingzhong Wang and Y A Tan

Information Sciences, Vol.265, pp.176-188

2014

DOI: https://doi.org/10.1016/j.ins.2013.11.021

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Abstract

search pattern

searchable encryption

cloud computing

fake query

grouping-based construction

Searching on remote encrypted data (commonly known as searchable encryption) has become an important issue in secure data outsourcing, since it allows users to outsource encrypted data to an untrusted third party while maintains the capability of keyword search on the data. Searchable encryption can be achieved using the classical method called oblivious RAM, but the resultant schemes are too inefficient to be applied in the real-world scenarios (e.g., cloud computing). Recently, a number of efficient searchable encryption schemes have been proposed under weaker security guarantees. Such schemes, however, still leak statistical information about the users' search pattern. In this paper, we first present two concrete attack methods to show that the search pattern leakage will result in such a situation: an adversary who has some auxiliary knowledge can uncover the underlying keywords of user queries. To address this issue, we then develop a grouping-based construction (GBC) to transform an existing searchable encryption scheme to a new scheme hiding the search pattern. Finally, experiments based on the real-world dataset demonstrate the effectiveness of our attack methods and the feasibility of our construction. © 2013 Elsevier Inc. All rights reserved.

Details

Title: Search pattern leakage in searchable encryption: Attacks and new construction
Authors: C Liu (Author) - Beijing Institute of Technology, China
L Zhu (Author) - Beijing Institute of Technology, China
Mingzhong Wang (Author) - Beijing Institute of Technology, China
Y A Tan (Author) - Beijing Institute of Technology, China
Publication details: Information Sciences, Vol.265, pp.176-188
Publisher: Elsevier Inc.
Date published: 2014
DOI: 10.1016/j.ins.2013.11.021
ISSN: 0020-0255
Organisation Unit: University of the Sunshine Coast, Queensland; USC Business School - Legacy; School of Science, Technology and Engineering
Language: English
Record Identifier: 99449582602621
Output Type: Journal article

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