FedClean: A Defense Mechanism Against Parameter Poisoning Attacks in Federated Learning

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Kumar , A , Khimani , V , Chatzopoulos , D & Hui , P 2022 , FedClean: A Defense Mechanism Against Parameter Poisoning Attacks in Federated Learning . in IEEE International Conference on Acoustics, Speech, and Signal Processing : ICASSP . IEEE International Conference on Acoustics, Speech, and Signal Processing proceedings , IEEE , IEEE International Conference on Acoustics, Speech, and Signal Processing , Singapore , 22/05/2022 . https://doi.org/10.1109/ICASSP43922.2022.9747497

Title: FedClean: A Defense Mechanism Against Parameter Poisoning Attacks in Federated Learning
Author: Kumar, Abhishek; Khimani, Vivek; Chatzopoulos, Dimitris; Hui, Pan
Contributor organization: Department of Computer Science
Publisher: IEEE
Date: 2022
Language: eng
Number of pages: 5
Belongs to series: IEEE International Conference on Acoustics, Speech, and Signal Processing
Belongs to series: IEEE International Conference on Acoustics, Speech, and Signal Processing proceedings
ISBN: 978-1-6654-0540-9
ISSN: 2379-190X
DOI: https://doi.org/10.1109/ICASSP43922.2022.9747497
URI: http://hdl.handle.net/10138/345968
Subject: 113 Computer and information sciences
Peer reviewed: Yes
Usage restriction: openAccess
Self-archived version: acceptedVersion


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