Nowadays most software applications have to deal with personal data, specially with the emergence of Web-based applications, where user profile information has become one of their main assets. Due to regulation laws and to protect the privacy of users, customers and companies; most of this information is considered private, and therefore convenient ways to gather, process and store them have to be proposed. A common problem when modeling software systems is the lack of support to specify how to enforce privacy concerns in data models. Current approaches for modeling privacy cover high-level privacy aspects to describe what should be done with the data (e.g., elements to be private) instead of how to do it (e.g., which privacy enhancing technology to use); or propose access control policies, which may cover privacy only partially. In this paper we propose a profile to define and enforce privacy concerns in UML class diagrams. Models annotated with our profile can be used in model-driven methodologies to generate privacy-aware applications.
CITATION STYLE
Cánovas Izquierdo, J. L., & Salas, J. (2018). A UML profile for privacy enforcement. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11176 LNCS, pp. 609–616). Springer Verlag. https://doi.org/10.1007/978-3-030-04771-9_46
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