文章基本信息

标题：Privacy- Preserving Keyword-based Semantic Search over Encrypted Cloud Data
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作者：Xingming Sun ; Yanling Zhu ; Zhihua Xia 等
期刊名称：International Journal of Security and Its Applications
印刷版ISSN：1738-9976
出版年度：2014
卷号：8
期号：3
页码：9-20
DOI：10.14257/ijsia.2014.8.3.02
出版社：SERSC
摘要：To protect the privacy, sensitive information has to be encrypted before outsourcing to the cloud. Thus the effective data utilization becomes a significant challenge. Searchable encryption scheme has been developed to conduct retrieval over encrypted data. However, these schemes only support exact keyword search. Recent fuzzy search schemes mainly evaluate the similarity of keywords from the structure but the semantic relatedness is not considered. Our work focuses on realizing secure semantic search through query keyword semantic extension. Based on the co-occurrence probability of terms, the semantic relationship library is constructed to record the semantic similarity between keywords. We exploited architecture of two clouds, namely private cloud and public cloud. The search operation is divided into two steps. The first step expands the query keyword upon SRL stored in the private cloud. The second step uses the extended query keywords set to retrieve the index on public cloud. Finally the matched files are returned in order. Detailed security analysis shows that our solution is privacy-preserving and secure. Experimental evaluation demonstrates the efficiency and effectives of the scheme.
关键词：secure; rank; keyword-based; semantic similarity; encrypted cloud data