Cargando…
Anatomisation with slicing: a new privacy preservation approach for multiple sensitive attributes
An enormous quantity of personal health information is available in recent decades and tampering of any part of this information imposes a great risk to the health care field. Existing anonymization methods are only apt for single sensitive and low dimensional data to keep up with privacy specifical...
Autores principales: | Susan, V. Shyamala, Christopher, T. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4932023/ https://www.ncbi.nlm.nih.gov/pubmed/27429874 http://dx.doi.org/10.1186/s40064-016-2490-0 |
Ejemplares similares
-
F-Classify: Fuzzy Rule Based Classification Method for Privacy Preservation of Multiple Sensitive Attributes
por: Attaullah, Hasina, et al.
Publicado: (2021) -
Sensitive attribute privacy preservation of trajectory data publishing based on l-diversity
por: Yao, Lin, et al.
Publicado: (2020) -
Privacy-preserving integration of multiple institutional data for single-cell type identification with scPrivacy
por: Chen, Shaoqi, et al.
Publicado: (2022) -
Privacy preserving linkage using multiple match-keys
por: Randall, SM, et al.
Publicado: (2019) -
A Privacy Attack on Multiple Dynamic Match-key based Privacy-Preserving Record Linkage
por: Vidanage, A, et al.
Publicado: (2020)