Toward Efficient Multi-Keyword Fuzzy Search Over Encrypted Outsourced Data With Accuracy Improvement

Keyword-based search over encrypted outsourced data has become an important tool in the current cloud computing scenario. The majority of the existing techniques are focusing on multi-keyword exact match or single keyword fuzzy search. However, those existing techniques find less practical significa...

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Vydané v:IEEE transactions on information forensics and security Ročník 11; číslo 12; s. 2706 - 2716
Hlavní autori: Fu, Zhangjie, Wu, Xinle, Guan, Chaowen, Sun, Xingming, Ren, Kui
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 01.12.2016
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Cats
Cryptography
Data models
fuzzy search
Indexes
Keywords
multi-keyword search
Outsourcing security
privacy-preserving
Search problems
searchable encryption
Servers
ISSN:1556-6013, 1556-6021
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Shrnutí:Keyword-based search over encrypted outsourced data has become an important tool in the current cloud computing scenario. The majority of the existing techniques are focusing on multi-keyword exact match or single keyword fuzzy search. However, those existing techniques find less practical significance in real-world applications compared with the multi-keyword fuzzy search technique over encrypted data. The first attempt to construct such a multi-keyword fuzzy search scheme was reported by Wang et al., who used locality-sensitive hashing functions and Bloom filtering to meet the goal of multi-keyword fuzzy search. Nevertheless, Wang's scheme was only effective for a one letter mistake in keyword but was not effective for other common spelling mistakes. Moreover, Wang's scheme was vulnerable to server out-of-order problems during the ranking process and did not consider the keyword weight. In this paper, based on Wang et al.'s scheme, we propose an efficient multi-keyword fuzzy ranked search scheme based on Wang et al.'s scheme that is able to address the aforementioned problems. First, we develop a new method of keyword transformation based on the uni-gram, which will simultaneously improve the accuracy and creates the ability to handle other spelling mistakes. In addition, keywords with the same root can be queried using the stemming algorithm. Furthermore, we consider the keyword weight when selecting an adequate matching file set. Experiments using real-world data show that our scheme is practically efficient and achieve high accuracy.
Bibliografia:ObjectType-Article-1
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ISSN:1556-6013
1556-6021
DOI:10.1109/TIFS.2016.2596138