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Fully Private Coded Matrix Multiplication From Colluding Workers

Authors
Kim, MinchulYang, HeecheolLee, Jungwoo
Issue Date
Mar-2021
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Keywords
Coded computation; cross subspace alignment; private information retrieval
Citation
IEEE COMMUNICATIONS LETTERS, v.25, no.3, pp.730 - 733
Journal Title
IEEE COMMUNICATIONS LETTERS
Volume
25
Number
3
Start Page
730
End Page
733
URI
https://scholarworks.bwise.kr/kumoh/handle/2020.sw.kumoh/19043
DOI
10.1109/LCOMM.2020.3037744
ISSN
1089-7798
Abstract
Recently, coded computation has been used to reduce the completion time in distributed computing by mitigating straggler effects with erasure codes. As a variation of coded computation, fully private coded matrix multiplication (FPCMM) has been proposed to preserve a master's privacy in a scenario where the master wants to obtain a matrix multiplication result from the libraries which are shared at the workers, while concealing both of the two indices of the desired matrices from each worker. In this letter, we propose a new FPCMM scheme to keep a master's privacy from up to T colluding workers. Furthermore, we compare the performance of our scheme with those of the existing private coded matrix multiplication schemes for non-colluding workers and for concealing the index of a single desired matrix.
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