Blockchain Empowered Differentially Private and Auditable Data Publishing in Industrial IoT

Lei Xu, Ting Bao, Liehuang Zhu*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

As more and more organizations deploy their sensing devices in the industrial Internet of Things network, it becomes increasingly important for the organizations to share data with others, so that the value of the data can be fully explored. However, individuals' privacy may be compromised because of data sharing. In this article, we study the differentially private data publishing problem, which aims at balancing between privacy and data utility. Specifically, two blockchain-based data publishing protocols are proposed. For histogram publishing, we propose a protocol where the Laplace noise added in the query result is verified by the blockchain. For anonymized data publishing, we propose a protocol, which can prevent the publisher and the recipient from lying about the utility of the published data. With the blockchain acting as a reliable intermediary between the publisher and the recipient, the proposed protocols can help to realize fair and auditable data sharing.

Original languageEnglish
Article number9294114
Pages (from-to)7659-7668
Number of pages10
JournalIEEE Transactions on Industrial Informatics
Volume17
Issue number11
DOIs
Publication statusPublished - Nov 2021

Keywords

  • Blockchain
  • Differential privacy
  • Histogram publishing
  • Transaction verification
  • Verifiable shuffle

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