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Author Samee, Zahur ♦ Jack, Doerner ♦ David, Evans ♦ Borja, Balle ♦ Mariana, Raykova ♦ Phillipp, Schoppmann ♦ Adrià, Gascón
Source Directory of Open Access Journals (DOAJ)
Content type Text
Publisher Sciendo
File Format HTM / HTML
Date Created 2017-11-01
Copyright Year ©2017
Language English
Subject Domain (in LCC) BJ1-1725 ♦ QA75.5-76.95
Subject Keyword Computer science ♦ Instruments and machines ♦ Psychology ♦ Electronic computers ♦ Mathematics ♦ Science ♦ Ethics ♦ Philosophy ♦ Religion
Abstract We propose privacy-preserving protocols for computing linear regression models, in the setting where the training dataset is vertically distributed among several parties. Our main contribution is a hybrid multi-party computation protocol that combines Yao’s garbled circuits with tailored protocols for computing inner products. Like many machine learning tasks, building a linear regression model involves solving a system of linear equations. We conduct a comprehensive evaluation and comparison of different techniques for securely performing this task, including a new Conjugate Gradient Descent (CGD) algorithm. This algorithm is suitable for secure computation because it uses an efficient fixed-point representation of real numbers while maintaining accuracy and convergence rates comparable to what can be obtained with a classical solution using floating point numbers. Our technique improves on Nikolaenko et al.’s method for privacy-preserving ridge regression (S&P 2013), and can be used as a building block in other analyses. We implement a complete system and demonstrate that our approach is highly scalable, solving data analysis problems with one million records and one hundred features in less than one hour of total running time.
ISSN 22990984
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2017-10-01
e-ISSN 22990984
Journal Proceedings on Privacy Enhancing Technologies
Volume Number 2017
Issue Number 4
Page Count 20
Starting Page 345
Ending Page 364


Source: Directory of Open Access Journals (DOAJ)