4.7 Article

A Practical Framework for Secure Document Retrieval in Encrypted Cloud File Systems

期刊

出版社

IEEE COMPUTER SOC
DOI: 10.1109/TPDS.2021.3107752

关键词

Cloud computing; Servers; Indexes; Security; Encryption; Search problems; Simulation; Cloud computing; privacy-preserving; searchable encryption; document ranked retrieval

资金

  1. National Natural Science Foundation of China [62001055, 62102017]
  2. Beijing Natural Science Foundation [4204107, A02B01C03-201902D0]

向作者/读者索取更多资源

This paper presents a new encrypted document retrieval system that integrates a proxy server to alleviate data owner's workload and improve the system's security level. By constructing different index trees and utilizing suitable algorithms, efficient search with multiple parameters is achieved.
With the development of cloud computing, more and more data owners are motivated to outsource their documents to the cloud and share them with the authorized data users securely and flexibly. To protect data privacy, the documents are generally encrypted before being outsourced to the cloud and hence their searchability decreases. Though many privacy-preserving document search schemes have been proposed, they cannot reach a proper balance among functionality, flexibility, security and efficiency. In this paper, a new encrypted document retrieval system is designed and a proxy server is integrated into the system to alleviate data owner's workload and improve the whole system's security level. In this process, we consider a more practical and stronger threat model in which the cloud server can collude with a small number of data users. To support multiple document search patterns, we construct two AVL trees for the filenames and authors, and a Hierarchical Retrieval Features tree (HRF tree) for the document vectors. A depth-first search algorithm is designed for the HRF tree and the Enhanced Asymmetric Scalar-Product-Preserving Encryption (Enhanced ASPE) algorithm is utilized to encrypt the HRF tree. All the three index trees are linked with each other to efficiently support the search requests with multiple parameters. Theoretical analysis and simulation results illustrate the security and efficiency of the proposed framework.

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