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  4. Extending model-based privacy analysis for the industrial data space by exploiting privacy level agreements
 
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2018
Conference Paper
Title

Extending model-based privacy analysis for the industrial data space by exploiting privacy level agreements

Abstract
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.
Author(s)
Ahmadian, Amir Shayan
Jürjens, Jan  
Fraunhofer-Institut für Software- und Systemtechnik ISST  
Strüber, Daniel
Mainwork
SAC '18, 33rd ACM/SIGAPP Symposium On Applied Computing. Proceedings  
Conference
Symposium on Applied Computing (SAC) 2018  
DOI
10.1145/3167132.3167256
Language
English
Fraunhofer-Institut für Software- und Systemtechnik ISST  
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