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Homomorphic Training of 30,000 Logistic Regression Models
Approximate numbers Homomorphic encryption GWAS
2019/4/28
In this work, we demonstrate the use the CKKS homomorphic encryption scheme to train a large number of logistic regression models simultaneously, as needed to run a genome-wide association study (GWAS...
Semi-parallel Logistic Regression for GWAS on Encrypted Data
Homomorphic encryption Genome-wide association studies Logistic regression
2019/3/21
The sharing of biomedical data is crucial to enable scientific discoveries across institutions and improve health care. For example, genome-wide association studies (GWAS) based on a large number of s...
Privacy-preserving semi-parallel logistic regression training with Fully Homomorphic Encryption
fully homomorphic encryption logistic regression genome privacy
2019/2/27
Background Privacy-preserving computations on genomic data, and more generally on medical data, is a critical path technology for innovative, life-saving research to positively and equally impact the ...
Efficient Logistic Regression on Large Encrypted Data
implementation machine learning homomorphic encryption
2018/7/10
Machine learning on encrypted data is a cryptographic method for analyzing private and/or sensitive data while keeping privacy. In the training phase, it takes as input an encrypted training data and ...
Logistic regression over encrypted data from fully homomorphic encryption
homomorphic encryption logistic regression
2018/5/22
More precisely, given a list of approximately 15001500 patient records, each with 1818 binary features containing information on specific mutations, the idea was for the data holder to encrypt the rec...
Logistic Regression Model Training based on the Approximate Homomorphic Encryption
homomorphic encryption machine learning logistic regression
2018/3/8
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 c...
Doing Real Work with FHE: The Case of Logistic Regression
Homomorphic Encryption Implementation Logistic Regression
2018/3/5
We describe our recent experience, building a system that uses fully-homomorphic encryption (FHE) to approximate the coefficients of a logistic-regression model, built from genomic data. The aim of th...
Logistic regression is a popular technique used in machine learning to construct classification models. Since the construction of such models is based on computing with large datasets, it is an appeal...
Secure Logistic Regression based on Homomorphic Encryption
Homomorphic encryption approximate arithmetic logistic regression
2018/1/19
Learning a model without accessing raw data has been an intriguing idea to the security and machine learning researchers for years. In an ideal setting, we want to encrypt sensitive data to store them...
Efficient and Private Scoring of Decision Trees, Support Vector Machines and Logistic Regression Models based on Pre-Computation
privacy-preserving private data
2016/7/29
Many data-driven personalized services require that private data of users is scored against a trained machine learning model. In this paper we propose a novel protocol for privacy-preserving classific...
Scalable and Secure Logistic Regression via Homomorphic Encryption
Logistic regression homomorphic encryption Paillier
2016/2/23
Logistic regression is a powerful machine learning tool to classify data. When dealing with
sensitive data such as private or medical information, cares are necessary. In this paper, we propose
a se...