Making GDPR usable: A model to support usability evaluations of privacy
2020 (English) In: IFIP Advances in Information and Communication Technology, Springer, 2020, p. 275-291Conference paper, Published paper (Refereed)
Abstract [en]
We introduce a new model for evaluating privacy that builds on the criteria proposed by the EuroPriSe certification scheme by adding usability criteria. Our model is visually represented through a cube, called Usable Privacy Cube (or UP Cube), where each of its three axes of variability captures, respectively: rights of the data subjects, privacy principles, and usable privacy criteria. We slightly reorganize the criteria of EuroPriSe to fit with the UP Cube model, i.e., we show how EuroPriSe can be viewed as a combination of only rights and principles, forming the two axes at the basis of our UP Cube. In this way we also want to bring out two perspectives on privacy: that of the data subjects and, respectively, that of the controllers/processors. We define usable privacy criteria based on usability goals that we have extracted from the whole text of the General Data Protection Regulation. The criteria are designed to produce measurements of the level of usability with which the goals are reached. Precisely, we measure effectiveness, efficiency, and satisfaction, considering both the objective and the perceived usability outcomes, producing measures of accuracy and completeness, of resource utilization (e.g., time, effort, financial), and measures resulting from satisfaction scales. In the long run, the UP Cube is meant to be the model behind a new certification methodology capable of evaluating the usability of privacy, to the benefit of common users. For industries, considering also the usability of privacy would allow for greater business differentiation, beyond GDPR compliance.
Place, publisher, year, edition, pages Springer, 2020. p. 275-291
Keywords [en]
GDPR, Human-Computer Interaction, Privacy certification, Usability goals, Usable privacy, Usable privacy criteria, Computer privacy, Data visualization, Geometry, Human computer interaction, Selenium compounds, Usability engineering, General data protection regulations, Perceived usability, Privacy principle, Resource utilizations, Usability evaluation, Data privacy
National Category
Computer Sciences
Identifiers URN: urn:nbn:se:kau:diva-77637 DOI: 10.1007/978-3-030-42504-3_18 Scopus ID: 2-s2.0-85082388673 ISBN: 9783030425036 (print) OAI: oai:DiVA.org:kau-77637 DiVA, id: diva2:1426292
Conference 14th IFIP International Summer School on Privacy and Identity Management, 2019; Windisch; Switzerland; 19 August 2019 through 23 August 2019; Code 238439
2020-04-242020-04-242020-05-11 Bibliographically approved