Towards Mutual Trust-Based Matching For Federated Learning Client Selection-Reference-Cited by-同舟云学术

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Towards Mutual Trust-Based Matching For Federated Learning Client Selection

Published:2023-06-19 Issue: Volume: Page:
ISSN:
Container-title:2023 International Wireless Communications and Mobile Computing (IWCMC)
language:
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Author:

Wehbi Osama¹,Wahab Omar Abdel²,Mourad Azzam³,Otrok Hadi⁴,Alkhzaimi Hoda⁵,Guizani Mohsen¹

Affiliation:

1. Mohammad Bin Zayed University of Artificial Intelligence,Abu Dhabi,UAE

2. Polytechnique Montréal, Montreal,Department of Computer and Software Engineering,Quebec,Canada

3. Lebanese American University,Cyber Security Systems and Applied AI Research Center,Department of CSM,Lebanon

4. Khalifa University,Center of Cyber-Physical Systems (C2PS),Department of EECS,Abu Dhabi,UAE

5. New York University,Division of Engineering,Abu Dhabi,UAE

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10182387/10182368/10182581.pdf?arnumber=10182581

Reference24 articles.

1. Federated learning: Strategies for improving communication efficiency;kone?n`’y;arXiv preprint arXiv 1610 05492,2016

2. ModularFed: Leveraging modularity in federated learning frameworks

3. FEDGAN-IDS: Privacy-preserving IDS using GAN and Federated Learning

4. An endorsement-based trust bootstrapping approach for newcomer cloud services

5. Communication-efficient learning of deep networks from decentralized data;mcmahan;Artificial Intelligence and Statistics,2017

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