TY - GEN
T1 - Privacy-preserving multi-keyword fuzzy search over encrypted data in the cloud
AU - Wang, Bing
AU - Yu, Shucheng
AU - Lou, Wenjing
AU - Hou, Y. Thomas
PY - 2014
Y1 - 2014
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84904421834&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84904421834&partnerID=8YFLogxK
U2 - 10.1109/INFOCOM.2014.6848153
DO - 10.1109/INFOCOM.2014.6848153
M3 - Conference contribution
AN - SCOPUS:84904421834
SN - 9781479933600
T3 - Proceedings - IEEE INFOCOM
SP - 2112
EP - 2120
BT - IEEE INFOCOM 2014 - IEEE Conference on Computer Communications
T2 - 33rd IEEE Conference on Computer Communications, IEEE INFOCOM 2014
Y2 - 27 April 2014 through 2 May 2014
ER -