Semantic Multi-Keyword Search over Encrypted Cloud Data with Privacy Preservation
Fei-Ju Hsieh, Tai-Lin Chin, Chin-Ya Huang, Shan-Hsiang Shen, Chung-An Shen · 2019
Cloud storage provides the great convenience for people to access their data at anytime from any place. Since cloud storage is usually run by the third-party service provider, keyword search over cloud data with privacy protection is of great importance. Many studies in the literature have proposed keyword search scheme for document search, but, in most schemes, the query keywords must exactly match those in the document indexes. However, it is impractical to restrict query keywords provided by the user when performing the search. This paper proposes the scheme for semantic multi-keyword search over encrypted cloud data. Users are able to select query keywords on their own choice. In addition, the query privacy of the user and the security of the documents are protected simultaneously through encrypted document search to prevent snooping from the cloud service provider. Experiments are conducted using a dataset of massive real world papers. The results show that the proposed scheme can effectively perform the semantic multi-keyword search over encrypted cloud data with great efficiency.