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Secure Logistic Regression Based on Homomorphic Encryption: Design and Evaluation

BACKGROUND: Learning a model without accessing raw data has been an intriguing idea to security and machine learning researchers for years. In an ideal setting, we want to encrypt sensitive data to store them on a commercial cloud and run certain analyses without ever decrypting the data to preserve...

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Detalhes bibliográficos
Publicado no:JMIR Med Inform
Main Authors: Kim, Miran, Song, Yongsoo, Wang, Shuang, Xia, Yuhou, Jiang, Xiaoqian
Formato: Artigo
Idioma:Inglês
Publicado em: JMIR Publications 2018
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC5930176/
https://ncbi.nlm.nih.gov/pubmed/29666041
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.2196/medinform.8805
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