DocumentCode :
2996789
Title :
A Fast Privacy-Preserving Multi-keyword Search Scheme on Cloud Data
Author :
Ce Yang ; Weiming Zhang ; Jun Xu ; Jiajia Xu ; Nenghai Yu
Author_Institution :
Electron. Eng. & Inf. Sci., Univ. of Sci. & Technol. of China, Hefei, China
fYear :
2012
fDate :
22-24 Nov. 2012
Firstpage :
104
Lastpage :
110
Abstract :
Nowadays, more and more people outsource their data to cloud servers for great flexibility and economic savings. Due to considerations on security, private data is usually protected by encryption before sending to cloud. How to utilize data efficiently while preserving user´s privacy is a new challenge. In this paper, we focus on a efficient multi-keyword search scheme meeting a strict privacy requirement. First, we make a short review of two existing schemes supporting multi-keyword search, the kNN-based MRSE scheme and scheme based on bloom filter. Based on the kNN-based scheme, we propose an improved scheme. Our scheme adopt a product of three sparse matrix pairs instead of the original dense matrix pair to encrypt index, and thus get a significant improvement in efficiency. Then, we combine our improved scheme with bloom filter, and thus gain the ability for index updating. Simulation Experiments show proposed scheme indeed introduces low overhead on computation and storage.
Keywords :
cloud computing; cryptography; data privacy; data structures; information retrieval; sparse matrices; bloom filter; cloud data; cloud servers; encryption; fast privacy-preserving multikeyword search scheme; kNN-based MRSE scheme; kNN-based multi-keyword ranked search over encrypted cloud; original dense matrix; private data; sparse matrix pairs; strict privacy requirement; Dictionaries; Encryption; Indexes; Privacy; Servers; Vectors; Cloud Security; Multi-keyword Search; Privacy-preserving; Searchalbe Encryption; Secure KNN;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cloud and Service Computing (CSC), 2012 International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4673-4724-2
Type :
conf
DOI :
10.1109/CSC.2012.23
Filename :
6414485
Link To Document :
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