Transforming Data Flow Diagrams for Privacy Compliance (Long Version)

November 24, 2020 Β· Declared Dead Β· πŸ› International Conference on Model-Driven Engineering and Software Development

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Authors Hanaa Alshareef, Sandro Stucki, Gerardo Schneider arXiv ID 2011.12028 Category cs.SE: Software Engineering Citations 6 Venue International Conference on Model-Driven Engineering and Software Development Last Checked 4 months ago
Abstract
Recent regulations, such as the European General Data Protection Regulation (GDPR), put stringent constraints on the handling of personal data. Privacy, like security, is a non-functional property, yet most software design tools are focused on functional aspects, using for instance Data Flow Diagrams (DFDs). In previous work, a conceptual model was introduced where DFDs could be extended into so-called Privacy-Aware Data Flow Diagrams (PA-DFDs) with the aim of adding specific privacy checks to existing DFDs. In this paper, we provide an explicit algorithm and a proof-of-concept implementation to transform DFDs into PA-DFDs. Our tool assists software engineers in the critical but error-prone task of systematically inserting privacy checks during design (they are automatically added by our tool) while still allowing them to inspect and edit the. PA-DFD if necessary. We have also identified and addressed ambiguities and inaccuracies in the high-level transformation proposed in previous work. We apply our approach to two realistic applications from the construction and online retail sectors.
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