|Publisher DOI:||10.1145/3538969.3539010||Title:||Precise Analysis of Purpose Limitation in Data Flow Diagrams||Language:||English||Authors:||Alshareef, Hanaa
|Keywords:||data flow diagram; Privacy by design; purpose limitation||Issue Date:||Aug-2022||Source:||17th International Conference on Availability, Reliability and Security (ARES 2022)||Abstract (english):||
Data Flow Diagrams (DFDs) are primarily used for modelling functional properties of a system. In recent work, it was shown that DFDs can be used to also model non-functional properties, such as security and privacy properties, if they are annotated with appropriate security- and privacy-related information. An important privacy principle one may wish to model in this way is purpose limitation. But previous work on privacy-aware DFDs (PA-DFDs) considers purpose limitation only superficially, without explaining how the purpose of DFD activators and flows ought to be specified, checked or inferred. In this paper, we define a rigorous formal framework for (1) annotating DFDs with purpose labels and privacy signatures, (2) checking the consistency of labels and signatures, and (3) inferring labels from signatures. We implement our theoretical framework in a proof-of concept tool consisting of a domain-specific language (DSL) for specifying privacy signatures and algorithms for checking and inferring purpose labels from such signatures. Finally, we evaluate our framework and tool through a case study based on a DFD from the privacy literature.
|Conference:||17th International Conference on Availability, Reliability and Security, ARES 2022||URI:||http://hdl.handle.net/11420/13575||ISBN:||978-145039670-7||Institute:||Software Security E-22||Document Type:||Chapter/Article (Proceedings)||Project:||Assurance and certification in secure Multi-party Open Software and Services|
|Appears in Collections:||Publications without fulltext|
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