Cryptology ePrint Archive: Report 2018/433

Achieving Fine-grained Multi-keyword Ranked Search over Encrypted Cloud Data

Guowen Xu and Hongwei Li

Abstract: With the advancement of Cloud computing, people now store their data on remote Cloud servers for larger computation and storage resources. However, users’ data may contain sensitive information of users and should not be disclosed to the Cloud servers. If users encrypt their data and store the encrypted data in the servers, the search capability supported by the servers will be significantly reduced because the server has no access to the data content. In this paper, we propose a Fine-grained Multi-keyword Ranked Search (FMRS) scheme over encrypted Cloud data. Specifically, we leverage novel techniques to realize multikeyword ranked search, which supports both mixed “AND”, “OR” and “NO” operations of keywords and ranking according to the preference factor and relevance score. Through security analysis, we can prove that the data confidentiality, privacy protection of index and trapdoor, and the unlinkability of trapdoor can be achieved in our FMRS. Besides, Extensive experiments show that the FMRS possesses better performance than existing schemes in terms of functionality and efficiency.

Category / Keywords: secret-key cryptography

Date: received 9 May 2018, last revised 14 May 2018

Contact author: guowen xu at foxmail com

Available format(s): PDF | BibTeX Citation

Version: 20180514:170038 (All versions of this report)

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