Transforming Data Flow Diagrams for Privacy Compliance

Alshareef, Hanaa; Stucki, Sandro; Schneider, Gerardo

doi:10.5220/0010255002070215

Cited by 3 publications

(9 citation statements)

References 13 publications

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“…Antignac et al [6,7] extended DFDs with a data deletion type of flow and a data structure to specify personal data: (i) the owner of personal data, (ii) the Reason' P Fig. 2: Selection of B-DFD flow types and corresponding transformation rules [5].…”

Section: Preliminariesmentioning

confidence: 99%

“…Building on that work, we defined and implemented an algorithm for transforming B-DFDs into PA-DFDs [5]. The transformation is rule-based, with one rule for every type of B-DFD flow.…”

Section: Preliminariesmentioning

confidence: 99%

“…Following our previous work on PA-DFDs [5], we formally represent DFDs as attributed multigraphs with activators as nodes and flows as edges. 2) = CP1.…”

Section: Refinement Of Attributed Multigraphsmentioning

confidence: 99%

“…In earlier work, we described a Type-inference algorithm for checking the wellformedness of B-DFDs [5]. Here we introduce algorithms for checking the validity of a given abstraction map between abstract and concrete B-DFDs and for finding all possible abstraction maps between a pair of B-DFDs.…”

Section: B-dfd Refinementmentioning

confidence: 99%

“…Antignac et al outlined their transformation from B-DFDs to PA-DFDs through set of high-level graphical "rules". A full algorithm and reference implementation were later provided by Alshareef et al [5]. B-DFDs have been shown to be useful for software engineers when designing functional properties, and the privacy-enhanced PA-DFDs are a step towards adding specific non-functional aspects to such designs.…”

Section: Introductionmentioning

confidence: 99%

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Refining Privacy-Aware Data Flow Diagrams

Alshareef

Stucki

Schneider

2021

Lecture Notes in Computer Science

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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 were extended into so-called Privacy-Aware Data Flow Diagrams (PA-DFDs) with the aim of adding specific privacy checks to existing DFDs. An implementation to add such automatic checks has also been developed. In this paper, we define the notion of refinement for both DFDs and PA-DFDs as a special type of structure-preserving map (or graph homomorphism). We also provide three algorithms to find, check and transform refinements, and we show that the standard diagram "transform→refine / refine→transform" commutes. We have implemented our algorithms in a proof-of-concept tool called DFD Refinery, and have applied it to realistic scenarios.

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Section: Preliminariesmentioning

confidence: 99%

“…Building on that work, we defined and implemented an algorithm for transforming B-DFDs into PA-DFDs [5]. The transformation is rule-based, with one rule for every type of B-DFD flow.…”

Section: Preliminariesmentioning

confidence: 99%

“…Following our previous work on PA-DFDs [5], we formally represent DFDs as attributed multigraphs with activators as nodes and flows as edges. 2) = CP1.…”

Section: Refinement Of Attributed Multigraphsmentioning

confidence: 99%

Section: B-dfd Refinementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations