This paper presents new and efficient protocols for privacy preserving machine learning for linear regression, logistic regression and neural network training

Jun 18, 2016 · Vertically Partitioned Datasets. Secure Linear Regression on ... o Vertically partitioned datasets. • Tailored protocol for Phase1. • Two party ...

May 11, 2020 · Bibliographic details on Secure Linear Regression on Vertically Partitioned Datasets.

When multiple parties collect data on different but related variables, they may seek to combine their in- formation to fit regression models. The parties ...

– Scalable MPC protocols for linear regression on vertically partitioned datasets (Section 3). We design, analyze, and evaluate two hybrid MPC protocols ...

This protocol allows data owners to estimate coefficients and standard errors of linear regressions, and to examine regression model diagnostics, without ...

Jan 25, 2021 · In this paper, we propose a privacy- preserving distributed analysis framework for handling missing data when data are vertically partitioned.

Abstract: This paper studies the feasibility of privacy-preserving data mining in epidemiological study. As for the data-mining algorithm, we focus on a ...

The idea of SSP protocol is quite simple, but it has been widely applied to solve many distributed data problems such as secure electronic voting system [6], ...

This work proposes a protocol for performing linear regression over a dataset that is distributed over multiple parties.