An Extended Framework of Privacy-Preserving Computation with Flexible Access Control

Wenxiu Ding, Rui Hu, Zheng Yan, Xinren Qian, Robert H. Deng, Laurence T. Yang, M. Dong

Research output: Contribution to journalArticleScientificpeer-review

6 Citations (Scopus)
74 Downloads (Pure)


Cloud computing offers various services based on outsourced data by utilizing its huge volume of resources and great computation capability. However, it also makes users lose full control over their data. To avoid the leakage of user data privacy, encrypted data are preferred to be uploaded and stored in the cloud, which unfortunately complicates data analysis and access control. In particular, few existing works consider the fine-grained access control over the computational results from ciphertexts. Though our previous work proposed a framework to support several basic computations (such as addition, multiplication and comparison Ding2017) with flexible access control, privacy-preserving division calculations over encrypted data, as a crucial operation in many statistical processes and machine learning algorithms, is neglected. In this paper, we propose four privacy-preserving division computation schemes with flexible access control to fill this gap, which can adapt to various application scenarios. Furthermore, we extend a division scheme over encrypted integers to support privacy-preserving division over multiple data types including fixed-point numbers and fractional numbers. Finally, we give their security proof and show their efficiency and superiority through comprehensive simulations and comparisons with existing work.
Original languageEnglish
Article number8894534
Pages (from-to)918-930
Number of pages13
Issue number2
Early online date2019
Publication statusPublished - Jun 2020
MoE publication typeA1 Journal article-refereed


  • Access control
  • Computational modeling
  • Cloud computing
  • Protocols
  • Servers
  • Encryption
  • Cloud Computing
  • Secure Division Computation
  • Privacy Preservation
  • Access Control
  • Data Security.

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