Paper Info
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.
Year
DOI
Venue
2018
10.1145/3167132.3167256
SAC 2018: Symposium on Applied Computing Pau France April, 2018
Keywords
Field
DocType
Privacy by Design, Model-based Privacy Analysis, Industrial Data Space, Personal Data, GDPR
Data space,Sovereignty,Privacy by Design,Computer security,Computer science,Privacy Level,Technological change,Privacy analysis,Software development,User privacy
Conference
ISBN
Citations 
PageRank 
978-1-4503-5191-1
2
0.38
References 
Authors
19
3
Name
Order
Citations
PageRank
Amir Shayan Ahmadian1182.68
Jan Jurjens216916.07
Daniel Strüber311621.50