Identifying Reliable Machines for Distributed Matrix-Vector Multiplication

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

Abstract

This paper considers a distributed computing framework, where the task of T matrix-vector products is distributed among n worker machines. External adversaries have access to a subset L (the cardinality of which is |L|) of these machines, and can maliciously perturb the result of each of their computations with probability α. To correctly recover each matrixvector product, the master has to identify a set (of a fixed cardinality) of 'unattacked' worker machines. Towards this end, this work proposes four schemes that aim at performing such an identification. These schemes are analyzed and compared under different regimes of (|L|,α) for the two cases when |L| is (1) known or (2) unknown at the master.

Original languageEnglish (US)
Title of host publication2022 IEEE International Symposium on Information Theory, ISIT 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages820-825
Number of pages6
ISBN (Electronic)9781665421591
DOIs
StatePublished - 2022
Event2022 IEEE International Symposium on Information Theory, ISIT 2022 - Espoo, Finland
Duration: Jun 26 2022Jul 1 2022

Publication series

Name2022 IEEE International Symposium on Information Theory (ISIT)

Conference

Conference2022 IEEE International Symposium on Information Theory, ISIT 2022
Country/TerritoryFinland
CityEspoo
Period6/26/227/1/22

Bibliographical note

Funding Information:
This research was supported in part by the U.S. National Science Foundation under Grants CCF-1907785 and CCF-1849757. 1This is different from the setting considered in [2] where the attackers can collaborate with each other.

Publisher Copyright:
© 2022 IEEE.

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