Evaluating the Strength of Genomic Privacy Metrics

dc.cclicenceCC-BY-NC-NDen
dc.contributor.authorWagner, Isabelen
dc.date.acceptance2016-11-28en
dc.date.accessioned2017-03-01T10:15:56Z
dc.date.available2017-03-01T10:15:56Z
dc.date.issued2017-02-06
dc.descriptionThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.en
dc.description.abstractThe genome is a unique identifier for human individuals. The genome also contains highly sensitive information, creating a high potential for misuse of genomic data (for example, genetic discrimination). In this paper, we investigate how genomic privacy can be measured in scenarios where an adversary aims to infer a person’s genomic markers by constructing probability distributions on the values of genetic variations. We measured the strength of privacy metrics by requiring that metrics are monotonic with increasing adversary strength and uncovered serious problems with several existing metrics currently used to measure genomic privacy. We provide suggestions on metric selection, interpretation, and visualization, and illustrate the work flow using case studies for three real-world diseases.en
dc.funderARCHERen
dc.identifier.citationWagner, I. (2017) Evaluating the strength of genomic privacy metrics. ACM Transactions on Privacy and Security (TOPS) 20 (1), Article 2en
dc.identifier.doihttps://doi.org/10.1145/3020003
dc.identifier.issn2471-2566
dc.identifier.urihttp://hdl.handle.net/2086/13355
dc.language.isoen_USen
dc.peerreviewedYesen
dc.projectide433en
dc.publisherACMen
dc.researchinstituteCyber Technology Institute (CTI)en
dc.subjectprivacy metricsen
dc.subjectgenomic privacyen
dc.subjectARCHERen
dc.titleEvaluating the Strength of Genomic Privacy Metricsen
dc.typeArticleen

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