Estimating the success of re-identifications in incomplete datasets using generative models.
Ontology highlight
ABSTRACT:
SUBMITTER: Rocher L
PROVIDER: S-EPMC6650473 | biostudies-other | 2019 Jul
REPOSITORIES: biostudies-other
Publications
Estimating the success of re-identifications in incomplete datasets using generative models.
Rocher Luc L Hendrickx Julien M JM de Montjoye Yves-Alexandre YA
Nature communications 20190723 1
While rich medical, behavioral, and socio-demographic data are key to modern data-driven research, their collection and use raise legitimate privacy concerns. Anonymizing datasets through de-identification and sampling before sharing them has been the main tool used to address those concerns. We here propose a generative copula-based method that can accurately estimate the likelihood of a specific person to be correctly re-identified, even in a heavily incomplete dataset. On 210 populations, our ...[more]
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