Secure Distributed Gram Matrix Multiplication

Okko Makkonen*, Camilla Hollanti

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

Abstract

The Gram matrix of a matrix A is defined as AAT (or ATA). Computing the Gram matrix is an important operation in many applications, such as linear regression with the least squares method, where the explicit solution formula includes the Gram matrix of the data matrix. Secure distributed matrix multiplication (SDMM) can be used to compute the product of two matrices using the help of worker servers. If a Gram matrix were computed using SDMM, the data matrix would need to be encoded twice, which causes an unnecessary overhead in the communication cost. We propose a new scheme for this purpose called secure distributed Gram matrix multiplication (SDGMM). It can leverage the advantages of computing a Gram matrix instead of a regular matrix product.

Original languageEnglish
Title of host publication2023 IEEE Information Theory Workshop, ITW 2023
PublisherIEEE
Pages192-197
Number of pages6
ISBN (Electronic)979-8-3503-0149-6
DOIs
Publication statusPublished - 2023
MoE publication typeA4 Conference publication
EventIEEE Information Theory Workshop - Saint-Malo, France
Duration: 23 Apr 202328 Apr 2023

Publication series

NameProceedings : information theory workshop
ISSN (Electronic)2475-4218

Conference

ConferenceIEEE Information Theory Workshop
Abbreviated titleITW
Country/TerritoryFrance
CitySaint-Malo
Period23/04/202328/04/2023

Fingerprint

Dive into the research topics of 'Secure Distributed Gram Matrix Multiplication'. Together they form a unique fingerprint.

Cite this