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An interaction model for de-identification of human data held by external custodians
conference contribution
posted on 2018-01-01, 00:00 authored by Andrew Simmons, Anju Kissoon Curumsing, Rajesh VasaRajesh VasaReuse 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.
History
Event
Association for Computing Machinery. Conference (30th : 2018 : Melbourne, Vic.)Series
Association for Computing Machinery ConferencePagination
23 - 26Publisher
Association for Computing MachineryLocation
Melbourne, Vic.Place of publication
New York, N.Y.Publisher DOI
Start date
2018-12-04End date
2018-12-07ISBN-13
9781450361880Language
engPublication classification
E1 Full written paper - refereedCopyright notice
2018, owner/author(s)Editor/Contributor(s)
G Buchanan, D StevensonTitle of proceedings
OzCHI '18 : Proceedings of the 30th Australian Conference on Computer-Human Interaction 2018Usage metrics
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No categories selectedKeywords
Security and privacyUsability in security and privacyHuman-centered computingUser modelsHeuristic evaluationsInterface design prototypingScience & TechnologyTechnologyComputer Science, CyberneticsComputer Science, Theory & MethodsComputer ScienceAnonymizationDe-identificationEmotionsPrivacyINFORMATION-SEEKINGSERENDIPITY
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