Privacy protection for data-driven smart manufacturing systems

Kok Seng Wong, Myung Ho Kim

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

The Industrial Internet of Things (IIoT) is a new industrial ecosystem that combines intelligent and autonomous machines, advanced predictive analytics, and machine-human collaboration to improve productivity, efficiency and reliability. The integration of industry and IoT creates various attack surfaces and new opportunities for data breaches. In the IIoT context, it will often be the case that data is considered sensitive. This is because data will encapsulate various aspects of industrial operation, including highly sensitive information about products, business strategies, and companies. The transition to more open network architectures and data sharing of IoT poses challenges in manufacturing and industrial markets. The loss of sensitive information can lead to significant business loss and cause reputational damage. In this paper, the authors discuss emerging issues that are related to IIoT data sharing, investigate possible technological solutions to hide sensitive information and discuss some privacy management techniques in smart manufacturing systems.

Original languageEnglish
Pages (from-to)17-32
Number of pages16
JournalInternational Journal of Web Services Research
Volume14
Issue number3
DOIs
Publication statusPublished - Jul 1 2017

Fingerprint

Industry
Network architecture
Ecosystems
Productivity
Internet of things
Predictive analytics

Keywords

  • Data hiding
  • Data privacy protection
  • Industrial internet of things (IIoT)
  • Internet of things (IoT)
  • Secure data sharing
  • Smart manufacturing

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Computer Networks and Communications

Cite this

Privacy protection for data-driven smart manufacturing systems. / Wong, Kok Seng; Kim, Myung Ho.

In: International Journal of Web Services Research, Vol. 14, No. 3, 01.07.2017, p. 17-32.

Research output: Contribution to journalArticle

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