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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.<\/jats:p>","DOI":"10.4018\/ijwsr.2017070102","type":"journal-article","created":{"date-parts":[[2017,6,9]],"date-time":"2017-06-09T14:22:14Z","timestamp":1497018134000},"page":"17-32","source":"Crossref","is-referenced-by-count":35,"title":["Privacy Protection for Data-Driven Smart Manufacturing Systems"],"prefix":"10.4018","volume":"14","author":[{"given":"Kok-Seng","family":"Wong","sequence":"first","affiliation":[{"name":"School of Software, Soongsil University, Seoul, South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Myung Ho","family":"Kim","sequence":"additional","affiliation":[{"name":"School of Software, Soongsil University, Seoul, South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"IJWSR.2017070102-0","doi-asserted-by":"publisher","DOI":"10.3390\/s150820316"},{"key":"IJWSR.2017070102-1","unstructured":"Atos. 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