This paper presents a holistic approach to the realisation of Privacy by Design in workflow environments, ensuring that workflow models are rendered privacy-aware already at their specification phase. In this direction, the proposed framework, considering the particular technical requirements stemming from data protection principles, is centred around the following features: a novel, ontology-based approach to workflow modelling, which manages, unlike all other existing technologies, to adequately capture privacy aspects pertaining to workflow execution; the appropriate codification of privacy requirements into compliance rules and directives; an automated procedure for the verification of workflow models and their subsequent transformation, if needed, so that they become inherently privacy-aware before being deployed for execution.
CITATION STYLE
Koukovini, M. N., Papagiannakopoulou, E. I., Lioudakis, G. V., Dellas, N., Kaklamani, D. I., & Venieris, I. S. (2015). Towards inherent privacy awareness in workflows. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8872, pp. 95–113). Springer Verlag. https://doi.org/10.1007/978-3-319-17016-9_7
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