Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/630258
Title: Enabling Personalized Search over Encrypted Outsourced Data with Efficiency Improvement
Authors: Zhangjie Fu;Kui Ren;Jiangang Shu;Xingming Sun;Fengxiao Huang
subject: personalized search|Cloud security|outsourcing security|user interest model
Year: 2016
Publisher: IEEE
Abstract: In cloud computing, searchable encryption scheme over outsourced data is a hot research field. However, most existing works on encrypted search over outsourced cloud data follow the model of “one size fits all” and ignore personalized search intention. Moreover, most of them support only exact keyword search, which greatly affects data usability and user experience. So how to design a searchable encryption scheme that supports personalized search and improves user search experience remains a very challenging task. In this paper, for the first time, we study and solve the problem of personalized multi-keyword ranked search over encrypted data (PRSE) while preserving privacy in cloud computing. With the help of semantic ontology WordNet, we build a user interest model for individual user by analyzing the user's search history, and adopt a scoring mechanism to express user interest smartly. To address the limitations of the model of “one size fit all” and keyword exact search, we propose two PRSE schemes for different search intentions. Extensive experiments on real-world dataset validate our analysis and show that our proposed solution is very efficient and effective.
Description: 
URI: http://localhost/handle/Hannan/171082
http://localhost/handle/Hannan/630258
ISSN: 1045-9219
volume: 27
issue: 9
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7349214.pdf925.62 kBAdobe PDFThumbnail
Preview File
Title: Enabling Personalized Search over Encrypted Outsourced Data with Efficiency Improvement
Authors: Zhangjie Fu;Kui Ren;Jiangang Shu;Xingming Sun;Fengxiao Huang
subject: personalized search|Cloud security|outsourcing security|user interest model
Year: 2016
Publisher: IEEE
Abstract: In cloud computing, searchable encryption scheme over outsourced data is a hot research field. However, most existing works on encrypted search over outsourced cloud data follow the model of “one size fits all” and ignore personalized search intention. Moreover, most of them support only exact keyword search, which greatly affects data usability and user experience. So how to design a searchable encryption scheme that supports personalized search and improves user search experience remains a very challenging task. In this paper, for the first time, we study and solve the problem of personalized multi-keyword ranked search over encrypted data (PRSE) while preserving privacy in cloud computing. With the help of semantic ontology WordNet, we build a user interest model for individual user by analyzing the user's search history, and adopt a scoring mechanism to express user interest smartly. To address the limitations of the model of “one size fit all” and keyword exact search, we propose two PRSE schemes for different search intentions. Extensive experiments on real-world dataset validate our analysis and show that our proposed solution is very efficient and effective.
Description: 
URI: http://localhost/handle/Hannan/171082
http://localhost/handle/Hannan/630258
ISSN: 1045-9219
volume: 27
issue: 9
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7349214.pdf925.62 kBAdobe PDFThumbnail
Preview File
Title: Enabling Personalized Search over Encrypted Outsourced Data with Efficiency Improvement
Authors: Zhangjie Fu;Kui Ren;Jiangang Shu;Xingming Sun;Fengxiao Huang
subject: personalized search|Cloud security|outsourcing security|user interest model
Year: 2016
Publisher: IEEE
Abstract: In cloud computing, searchable encryption scheme over outsourced data is a hot research field. However, most existing works on encrypted search over outsourced cloud data follow the model of “one size fits all” and ignore personalized search intention. Moreover, most of them support only exact keyword search, which greatly affects data usability and user experience. So how to design a searchable encryption scheme that supports personalized search and improves user search experience remains a very challenging task. In this paper, for the first time, we study and solve the problem of personalized multi-keyword ranked search over encrypted data (PRSE) while preserving privacy in cloud computing. With the help of semantic ontology WordNet, we build a user interest model for individual user by analyzing the user's search history, and adopt a scoring mechanism to express user interest smartly. To address the limitations of the model of “one size fit all” and keyword exact search, we propose two PRSE schemes for different search intentions. Extensive experiments on real-world dataset validate our analysis and show that our proposed solution is very efficient and effective.
Description: 
URI: http://localhost/handle/Hannan/171082
http://localhost/handle/Hannan/630258
ISSN: 1045-9219
volume: 27
issue: 9
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7349214.pdf925.62 kBAdobe PDFThumbnail
Preview File