Privacy-preserving multi-keyword fuzzy search over encrypted data in the cloud

Bing Wang, Shucheng Yu, Wenjing Lou, Y. Thomas Hou

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

381 Scopus citations

Abstract

Enabling keyword search directly over encrypted data is a desirable technique for effective utilization of encrypted data outsourced to the cloud. Existing solutions provide multi-keyword exact search that does not tolerate keyword spelling error, or single keyword fuzzy search that tolerates typos to certain extent. The current fuzzy search schemes rely on building an expanded index that covers possible keyword misspelling, which lead to significantly larger index file size and higher search complexity. In this paper, we propose a novel multi-keyword fuzzy search scheme by exploiting the locality-sensitive hashing technique. Our proposed scheme achieves fuzzy matching through algorithmic design rather than expanding the index file. It also eliminates the need of a predefined dictionary and effectively supports multiple keyword fuzzy search without increasing the index or search complexity. Extensive analysis and experiments on real-world data show that our proposed scheme is secure, efficient and accurate. To the best of our knowledge, this is the first work that achieves multi-keyword fuzzy search over encrypted cloud data.

Original languageEnglish
Title of host publicationIEEE INFOCOM 2014 - IEEE Conference on Computer Communications
Pages2112-2120
Number of pages9
DOIs
StatePublished - 2014
Event33rd IEEE Conference on Computer Communications, IEEE INFOCOM 2014 - Toronto, ON, Canada
Duration: 27 Apr 20142 May 2014

Publication series

NameProceedings - IEEE INFOCOM
ISSN (Print)0743-166X

Conference

Conference33rd IEEE Conference on Computer Communications, IEEE INFOCOM 2014
Country/TerritoryCanada
CityToronto, ON
Period27/04/142/05/14

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