DROPFL: Client Dropout Attacks Against Federated Learning Under Communication Constraints
Author:
Affiliation:
1. Peking University,School of Software and Microelectronics & National Engineering Research Center for Software Engineering & PKU-OCTA Laboratory for Blockchain and Privacy Computing
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10445798/10445803/10446609.pdf?arnumber=10446609
Reference21 articles.
1. Distributed, decentralized, and democratized artificial intelligence
2. Communication-efficient learning of deep networks from decentralized data;McMahan,2017
3. Federated Learning for Healthcare: Systematic Review and Architecture Proposal
4. Federated Learning for Healthcare Informatics
5. Federated Learning for Internet of Things: A Comprehensive Survey
Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Enhancing Blockchain Security Against Data Tampering: Leveraging Hybrid Model in Multimedia Forensics and Multi-Party Computation for Supply Chain Data Protection;IEEE Access;2024
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