Cargando…
Logistic regression model training based on the approximate homomorphic encryption
BACKGROUND: Security concerns have been raised since big data became a prominent tool in data analysis. For instance, many machine learning algorithms aim to generate prediction models using training data which contain sensitive information about individuals. Cryptography community is considering se...
Autores principales: | Kim, Andrey, Song, Yongsoo, Kim, Miran, Lee, Keewoo, Cheon, Jung Hee |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6180367/ https://www.ncbi.nlm.nih.gov/pubmed/30309349 http://dx.doi.org/10.1186/s12920-018-0401-7 |
Ejemplares similares
-
Secure Logistic Regression Based on Homomorphic Encryption: Design and Evaluation
por: Kim, Miran, et al.
Publicado: (2018) -
Secure searching of biomarkers through hybrid homomorphic encryption scheme
por: Kim, Miran, et al.
Publicado: (2017) -
Privacy-preserving approximate GWAS computation based on homomorphic encryption
por: Kim, Duhyeong, et al.
Publicado: (2020) -
Logistic regression over encrypted data from fully homomorphic encryption
por: Chen, Hao, et al.
Publicado: (2018) -
Semi-Parallel logistic regression for GWAS on encrypted data
por: Kim, Miran, et al.
Publicado: (2020)