Query-Biased Preview over Outsourced and Encrypted Data
Joint Authors
Peng, Ningduo
Luo, Guangchun
Chen, Aiguo
Qin, Ke
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-08-31
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
For both convenience and security, more and moreusers encrypt their sensitive data before outsourcing it to a third party such as cloud storage service.
However, searching for the desired documents becomes problematic since it is costly to download and decrypt each possibly neededdocument to check if it contains the desired content.
An informative query-biased preview feature, as applied in modern search engine, could help the users to learn about the content without downloading the entire document.
However, when the data are encrypted, securely extracting a keyword-in-context snippet from the data as a preview becomes a challenge.
Based on private information retrieval protocol and the core concept of searchable encryption, we propose a single-server and two-round solution to securely obtain a query-biased snippet over the encrypted data from the server.
We achieve this novel result by making a document (plaintext) previewable under any cryptosystem and constructing a secure index to support dynamic computation for a best matched snippet when queried by some keywords.
For each document, the scheme has O(d) storage complexity and O(log(d/s)+s+d/s) communication complexity, where d is the document size and s is the snippet length.
American Psychological Association (APA)
Peng, Ningduo& Luo, Guangchun& Qin, Ke& Chen, Aiguo. 2013. Query-Biased Preview over Outsourced and Encrypted Data. The Scientific World Journal،Vol. 2013, no. 2013, pp.1-13.
https://search.emarefa.net/detail/BIM-1033380
Modern Language Association (MLA)
Peng, Ningduo…[et al.]. Query-Biased Preview over Outsourced and Encrypted Data. The Scientific World Journal No. 2013 (2013), pp.1-13.
https://search.emarefa.net/detail/BIM-1033380
American Medical Association (AMA)
Peng, Ningduo& Luo, Guangchun& Qin, Ke& Chen, Aiguo. Query-Biased Preview over Outsourced and Encrypted Data. The Scientific World Journal. 2013. Vol. 2013, no. 2013, pp.1-13.
https://search.emarefa.net/detail/BIM-1033380
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1033380