Privacy-preserving deduplication of encrypted data with dynamic ownership management in fog computing

Dongyoung Koo, Junbeom Hur

Research output: Contribution to journalArticlepeer-review

70 Citations (Scopus)


The explosion in the volume of data generated by end-point devices, arising from IoT proliferation, has lead to the adoption of data outsourcing to dedicated data centers. However, centralized data centers such as cloud storage cannot afford to manage large stores of data in a timely manner. To allow low latency access to large amounts of data, a new computing paradigm, called fog computing, has been introduced. In a fog computing environment, privacy issues surrounding outsourced data become more critical due to its complicated innards of the system. In addition, efficient resource management is another important criterion considering the application of pay-per-use in commercial fog storage. As an extension of cloud storage, most fog storage service providers will choose to adopt data deduplication techniques to minimize resource dissipation. At the same time, data owners may update or remove outsourced data stored in the remote storage to reduce expenses. In this paper, we propose the first privacy-preserving deduplication protocol capable of efficient ownership management in fog computing. It achieves fine-grained access control by introducing user-level key management and update mechanisms. Data-invariant user-level private keys enable data owners to maintain a constant number of keys regardless of the number of outsourced data files. The update of user-level public keys for valid data owners at the remote storage dramatically reduces communication overhead. Security and performance analyses demonstrate the efficiency of the proposed scheme in terms of communication and key management in fog storage.

Original languageEnglish
Pages (from-to)739-752
Number of pages14
JournalFuture Generation Computer Systems
Publication statusPublished - 2018 Jan

Bibliographical note

Funding Information:
We are grateful to the anonymous referees for their invaluable contributions to this article. This work was supported by a Korea University Grant. This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No. 2016R1A2A2A05005402).

Publisher Copyright:
© 2017 Elsevier B.V.


  • Data deduplication
  • Data ownership management
  • Data privacy
  • Efficiency
  • Fog computing

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications


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