Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/656017
Title: Toward Efficient Multi-Keyword Fuzzy Search Over Encrypted Outsourced Data With Accuracy Improvement
Authors: Zhangjie Fu;Xinle Wu;Chaowen Guan;Xingming Sun;Kui Ren
subject: multi-keyword search|fuzzy search|Outsourcing security|searchable encryption|privacy-preserving
Year: 2016
Publisher: IEEE
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.
URI: http://localhost/handle/Hannan/180523
http://localhost/handle/Hannan/656017
ISSN: 1556-6013
1556-6021
volume: 11
issue: 12
Appears in Collections:2016

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Title: Toward Efficient Multi-Keyword Fuzzy Search Over Encrypted Outsourced Data With Accuracy Improvement
Authors: Zhangjie Fu;Xinle Wu;Chaowen Guan;Xingming Sun;Kui Ren
subject: multi-keyword search|fuzzy search|Outsourcing security|searchable encryption|privacy-preserving
Year: 2016
Publisher: IEEE
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.
URI: http://localhost/handle/Hannan/180523
http://localhost/handle/Hannan/656017
ISSN: 1556-6013
1556-6021
volume: 11
issue: 12
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7524700.pdf1.23 MBAdobe PDFThumbnail
Preview File
Title: Toward Efficient Multi-Keyword Fuzzy Search Over Encrypted Outsourced Data With Accuracy Improvement
Authors: Zhangjie Fu;Xinle Wu;Chaowen Guan;Xingming Sun;Kui Ren
subject: multi-keyword search|fuzzy search|Outsourcing security|searchable encryption|privacy-preserving
Year: 2016
Publisher: IEEE
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.
URI: http://localhost/handle/Hannan/180523
http://localhost/handle/Hannan/656017
ISSN: 1556-6013
1556-6021
volume: 11
issue: 12
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7524700.pdf1.23 MBAdobe PDFThumbnail
Preview File