Based on model randomization and adaptive defense for federated learning schemes

Based on model randomization and adaptive defense for federated learning schemes

Abstract Federated Learning (FL) is a privacy-enhancing technique that enables multiple participants to collaboratively train machine learning models without sharing their local data. While FL is a promising paradigm, it is vulnerable to attacks targeting model updates and malicious behavior from cl...

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Bibliographic Details
Main Authors: Gaofeng Yue, Xiaowei Han
Format: Article
Language:English
Published: Nature Portfolio 2025-02-01
Series:Scientific Reports
Subjects:
Federated learning
Privacy preservation
Gradient randomization
Adaptive defensive
Online Access:https://doi.org/10.1038/s41598-024-84797-z
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https://doi.org/10.1038/s41598-024-84797-z

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