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dc.date.accessioned2020-12-05T20:10:45Z
dc.date.available2022-03-06T23:45:41Z
dc.date.created2020-11-30T12:58:01Z
dc.date.issued2020
dc.identifier.citationJohansen, Johanna Fischer-Hübner, Simone . Making GDPR Usable: A Model to Support Usability Evaluations of Privacy. Privacy and Identity Management. Data for Better Living: AI and Privacy. 2020, 275-291 Springer Nature
dc.identifier.urihttp://hdl.handle.net/10852/81447
dc.description.abstractWe 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.
dc.languageEN
dc.publisherSpringer Nature
dc.relation.ispartofIFIP Advances in Information and Communication Technology
dc.relation.ispartofseriesIFIP Advances in Information and Communication Technology
dc.titleMaking GDPR Usable: A Model to Support Usability Evaluations of Privacy
dc.typeChapter
dc.creator.authorJohansen, Johanna
dc.creator.authorFischer-Hübner, Simone
cristin.unitcode185,15,5,25
cristin.unitnamePROG Programmering
cristin.ispublishedtrue
cristin.fulltextpostprint
dc.identifier.cristin1854112
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.btitle=Privacy and Identity Management. Data for Better Living: AI and Privacy&rft.spage=275&rft.date=2020
dc.identifier.startpage275
dc.identifier.endpage291
dc.identifier.pagecount480
dc.identifier.doihttps://doi.org/10.1007/978-3-030-42504-3_18
dc.identifier.urnURN:NBN:no-84528
dc.type.documentBokkapittel
dc.type.peerreviewedPeer reviewed
dc.source.isbn978-3-030-42503-6
dc.identifier.fulltextFulltext https://www.duo.uio.no/bitstream/handle/10852/81447/2/main_final.pdf
dc.type.versionAcceptedVersion
cristin.btitlePrivacy and Identity Management. Data for Better Living: AI and Privacy
dc.relation.projectNFR/248113


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