MUSE: An Efficient and Accurate Verifiable Privacy-Preserving Multikeyword Text Search over Encrypted Cloud Data

With the development of cloud computing, services outsourcing in clouds has become a popular business model. However, due to the fact that data storage and computing are completely outsourced to the cloud service provider, sensitive data of data owners is exposed, which could bring serious privacy d...

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Bibliographic Details
Published in:Security and communication networks 2017-01, Vol.2017 (2017), p.1-17
Main Authors: Yang, Geng, Xun, Yi, Dai, Hua, Xiangyang, Zhu, Xiao, Li
Format: Article
Language:English
Subjects:
Access control
Accuracy
Algorithms
Business
Cloud computing
Clustering
Data encryption
Data storage
Debugging
Efficiency
Encryption
Keywords
Privacy
Search algorithms
Search process
Search strategies
Servers
Software
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Summary:With the development of cloud computing, services outsourcing in clouds has become a popular business model. However, due to the fact that data storage and computing are completely outsourced to the cloud service provider, sensitive data of data owners is exposed, which could bring serious privacy disclosure. In addition, some unexpected events, such as software bugs and hardware failure, could cause incomplete or incorrect results returned from clouds. In this paper, we propose an efficient and accurate verifiable privacy-preserving multikeyword text search over encrypted cloud data based on hierarchical agglomerative clustering, which is named MUSE. In order to improve the efficiency of text searching, we proposed a novel index structure, HAC-tree, which is based on a hierarchical agglomerative clustering method and tends to gather the high-relevance documents in clusters. Based on the HAC-tree, a noncandidate pruning depth-first search algorithm is proposed, which can filter the unqualified subtrees and thus accelerate the search process. The secure inner product algorithm is used to encrypted the HAC-tree index and the query vector. Meanwhile, a completeness verification algorithm is given to verify search results. Experiment results demonstrate that the proposed method outperforms the existing works, DMRS and MRSE-HCI, in efficiency and accuracy, respectively.
ISSN:1939-0114
1939-0122
DOI:10.1155/2017/1923476