@inproceedings{028f42c1b947445ea4787d52c6db964b,
title = "A New Generic Representation for Modeling Privacy",
abstract = "Verifying how personal data is used in industrial applications is of utmost importance for evaluating privacy. Existing works propose many definitions of privacy and offer a wide variety of approaches for verifying privacy properties. Yet, as far as we know, there is currently no generic setting allowing to model all these concepts, as well as to express and verify related privacy properties, whilst taking into account the various abstraction levels involved when designing and implementing a computer system. This work proposes a generic representation for modeling privacy relying on a new classification scheme and a new ontology. These aim to be generic enough for modeling key privacy concepts and their relationships, as well as helping express and verify related properties at different levels of abstractions. Our representation of privacy can also be specialized into various existing ones, according to different criteria, whilst allowing us to instantiate it for mapping its generic elements to existing examples or concrete use cases.",
keywords = "classification, consent, modeling language, ontology, privacy",
author = "Myriam Clouet and Thibaud Antignac and Mathilde Arnaud and Gabriel Pedroza and Julien Signoles",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 7th IEEE European Symposium on Security and Privacy Workshops, Euro S and PW 2022 ; Conference date: 06-06-2022 Through 10-06-2022",
year = "2022",
month = jan,
day = "1",
doi = "10.1109/EuroSPW55150.2022.00027",
language = "English",
series = "Proceedings - 7th IEEE European Symposium on Security and Privacy Workshops, Euro S and PW 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "203--211",
booktitle = "Proceedings - 7th IEEE European Symposium on Security and Privacy Workshops, Euro S and PW 2022",
}