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An interaction model for de-identification of human data held by external custodians
conference contributionposted on 01.01.2018, 00:00 authored by Andrew Simmons, Anju Kissoon CurumsingAnju Kissoon Curumsing, Rajesh VasaRajesh Vasa
Reuse of pre-existing industry datasets for research purposes requires a multi-stakeholder solution that balances the researcher's analysis objectives with the need to engage the industry data custodian, whilst respecting the privacy rights of human data subjects. Current methods place the burden on the data custodian, whom may not be sufficiently trained to fully appreciate the nuances of data de-identification. Through modelling of functional, quality, and emotional goals, we propose a de-identification in the cloud approach whereby the researcher proposes analyses along with the extraction and de-identification operations, while engaging the industry data custodian with secure control over authorising the proposed analyses. We demonstrate our approach through implementation of a de-identification portal for sports club data.
EventAssociation for Computing Machinery. Conference (30th : 2018 : Melbourne, Vic.)
SeriesAssociation for Computing Machinery Conference
Pagination23 - 26
PublisherAssociation for Computing Machinery
Place of publicationNew York, N.Y.
Publication classificationE1 Full written paper - refereed
Copyright notice2018, owner/author(s)
Editor/Contributor(s)G Buchanan, D Stevenson
Title of proceedingsOzCHI '18 : Proceedings of the 30th Australian Conference on Computer-Human Interaction 2018
Read the peer-reviewed publication
Security and privacyUsability in security and privacyHuman-centered computingUser modelsHeuristic evaluationsInterface design prototypingScience & TechnologyTechnologyComputer Science, CyberneticsComputer Science, Theory & MethodsComputer ScienceAnonymizationDe-identificationEmotionsPrivacyINFORMATION-SEEKINGSERENDIPITY