Privacy-preserving auditing scheme for shared data in public clouds

Libing Wu, Jing Wang, Sherali Zeadally, Debiao He

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


Recent advances in cloud storage have enabled users to outsource large amounts of data to a remote cloud server in order to reduce storage and management costs, and share files among many users in a group. However, how to efficiently audit the integrity of shared data while maintaining data privacy and user identity anonymity, is still a critical issue. We propose a novel public auditing scheme for data stored in a remote cloud server and shared among users in a large group. In particular, the proposed scheme incorporates group signature, homomorphic message authentication code to create data block tags, so that it can support public auditing and provide user identity anonymity. Furthermore, we use the random masking technique in the proposed scheme to preserve data privacy from the third-party auditor. The correctness and security analyses demonstrate that the proposed scheme is correct and provably secure under a robust security model. The performance evaluation and experimental results show that the proposed scheme is efficient while maintaining the desirable security properties.

Original languageEnglish
Pages (from-to)6156-6183
Number of pages28
JournalJournal of Supercomputing
Issue number11
StatePublished - Nov 1 2018

Bibliographical note

Publisher Copyright:
© 2018, Springer Science+Business Media, LLC, part of Springer Nature.


  • Cloud data
  • Identity anonymity
  • Privacy preservation
  • Public auditing

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Information Systems
  • Hardware and Architecture


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