FMDL: Federated Mutual Distillation Learning for Defending Backdoor Attacks

FMDL: Federated Mutual Distillation Learning for Defending Backdoor Attacks

Federated learning is a distributed machine learning algorithm that enables collaborative training among multiple clients without sharing sensitive information. Unlike centralized learning, it emphasizes the distinctive benefits of safeguarding data privacy. However, two challenging issues, namely h...

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Bibliographic Details
Main Authors: Hanqi Sun, Wanquan Zhu, Ziyu Sun, Mingsheng Cao, Wenbin Liu
Format: Article
Language:English
Published: MDPI AG 2023-11-01
Series:Electronics
Subjects:
federated learning
heterogeneous
backdoor attack
knowledge distillation
attention map
Online Access:https://www.mdpi.com/2079-9292/12/23/4838

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https://www.mdpi.com/2079-9292/12/23/4838

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