Journal
33RD ANNUAL ACM SYMPOSIUM ON APPLIED COMPUTING
Volume -, Issue -, Pages 1142-1149Publisher
ASSOC COMPUTING MACHINERY
DOI: 10.1145/3167132.3167256
Keywords
Privacy by Design; Model-based Privacy Analysis; Industrial Data Space; Personal Data; GDPR
Funding
- Design For Future Managed Software Evolution (DFG's SPP 1593) [JU 2734/2-2]
- Engineering Responsible Information Systems (University of Koblenz Landau)
- Industrial Data Space, German Ministry of Research [01IS15054]
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Considering the dramatic impact of the current technology changes on user privacy, it is important to contemplate privacy early on in software development. Ensuring privacy is particularly challenging in industrial ecosystems, in which an enterprise may depend on or cooperate with other enterprises to provide an IT service to a service customer. An example for such ecosystems is the Industrial Data Space (IDS). The IDS provides a basis for creating and using smart IT services, while ensuring digital sovereignty of service customers. In this paper, motivated by Article 25 of Regulation (EU) 2016/679 (GDPR), we apply a model-based privacy analysis approach to the IDS to enable the verification of conformance to customer's privacy preferences. To this end we extend an existing model-based privacy analysis to support customer's privacy preferences in compliance with the Article 5 of the GDPR. We also provide a privacy check to support the privacy of data exchanges between the enterprises. The approach is supported by the CARiSMA tool.
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