Secure linear regression algorithms: A comparison

Fida Dankar, Nisha Madathil

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The problem of secure linear regression calculation has been widely considered in the literature. It involves multiple parties, with a private dataset each, wanting to collectively carry out linear regression on the union of their datasets but are unable to combine the data due to privacy restrictions. The solutions suggested in the literature use different methods from cryptography to securely calculate the regression parameters while keeping the parties’ data private. In this paper, we compare the different algorithms in terms of security, efficiency and accuracy.

Original languageEnglish
Title of host publicationAdvances in Smart Technologies Applications and Case Studies - Selected Papers from the 1st International Conference on Smart Information and Communication Technologies, SmartICT 2019
EditorsAli El Moussati, Kidiyo Kpalma, Mohammed Ghaouth Belkasmi, Mohammed Saber, Sylvain Guégan
PublisherSpringer
Pages166-174
Number of pages9
ISBN (Print)9783030531867
DOIs
Publication statusPublished - 2020
Event1st International Conference on Smart Information and Communication Technologies, SmartICT 2019 - Berkane, Morocco
Duration: Sep 26 2019Sep 28 2019

Publication series

NameLecture Notes in Electrical Engineering
Volume684 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference1st International Conference on Smart Information and Communication Technologies, SmartICT 2019
Country/TerritoryMorocco
CityBerkane
Period9/26/199/28/19

Keywords

  • Data privacy
  • Linear regression
  • Secure multiparty computation

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering

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