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Privacy-preserving data sharing via probabilistic modeling

Differential privacy allows quantifying privacy loss resulting from accession of sensitive personal data. Repeated accesses to underlying data incur increasing loss. Releasing data as privacy-preserving synthetic data would avoid this limitation but would leave open the problem of designing what kin...

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Detalles Bibliográficos
Publicado en:Patterns (N Y)
Main Authors: Jälkö, Joonas, Lagerspetz, Eemil, Haukka, Jari, Tarkoma, Sasu, Honkela, Antti, Kaski, Samuel
Formato: Artigo
Idioma:Inglês
Publicado: Elsevier 2021
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Acceso en liña:https://ncbi.nlm.nih.gov/pmc/articles/PMC8276015/
https://ncbi.nlm.nih.gov/pubmed/34286296
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.patter.2021.100271
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