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
Autores principales: Jälkö, Joonas, Lagerspetz, Eemil, Haukka, Jari, Tarkoma, Sasu, Honkela, Antti, Kaski, Samuel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8276015/
https://www.ncbi.nlm.nih.gov/pubmed/34286296
http://dx.doi.org/10.1016/j.patter.2021.100271

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8276015/
https://www.ncbi.nlm.nih.gov/pubmed/34286296
http://dx.doi.org/10.1016/j.patter.2021.100271

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