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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Veröffentlicht in:	IEEE transactions on information forensics and security Jg. 11; H. 12; S. 2706 - 2716
Hauptverfasser:	Fu, Zhangjie, Wu, Xinle, Guan, Chaowen, Sun, Xingming, Ren, Kui
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.12.2016 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	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
Online-Zugang:	Volltext
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Abstract	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.
AbstractList	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.
Author	Zhangjie Fu Xinle Wu Kui Ren Chaowen Guan Xingming Sun
Author_xml	– sequence: 1 givenname: Zhangjie surname: Fu fullname: Fu, Zhangjie – sequence: 2 givenname: Xinle surname: Wu fullname: Wu, Xinle – sequence: 3 givenname: Chaowen surname: Guan fullname: Guan, Chaowen – sequence: 4 givenname: Xingming surname: Sun fullname: Sun, Xingming – sequence: 5 givenname: Kui surname: Ren fullname: Ren, Kui
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ContentType	Journal Article
Copyright	Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2016
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Snippet	Keyword-based search over encrypted outsourced data has become an important tool in the current cloud computing scenario. The majority of the existing...
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SubjectTerms	Cats Cryptography Data models fuzzy search Indexes Keywords multi-keyword search Outsourcing security privacy-preserving Search problems searchable encryption Servers
Title	Toward Efficient Multi-Keyword Fuzzy Search Over Encrypted Outsourced Data With Accuracy Improvement
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