Differentially Private Federated Learning: A Systematic Review

In recent years, privacy and security concerns in machine learning have promoted trusted federated learning to the forefront of research. Differential privacy has emerged as the de facto standard for privacy protection in federated learning due to its rigorous mathematical foundation and provable gu...

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Veröffentlicht in:	arXiv.org 2024-05
Hauptverfasser:	Fu, Jie, Yuan, Hong, Ling, Xinpeng, Wang, Leixia, Ran, Xun, Sun, Zhiyu, Wendy Hui Wang, Chen, Zhili, Cao, Yang
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Federated learning Machine learning Privacy Taxonomy
Online-Zugang:	Volltext
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