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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...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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JMIR Publications
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5930176/ https://www.ncbi.nlm.nih.gov/pubmed/29666041 http://dx.doi.org/10.2196/medinform.8805 |