Privacy attack in federated learning is not easy: an experimental study

Abstract Federated learning (FL) is an emerging distributed machine learning paradigm proposed for privacy preservation. Unlike traditional centralized learning approaches, FL enables multiple users to collaboratively train a shared global model without disclosing their own data, thereby significant...

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Bibliographic Details
Main Authors: Hangyu Zhu, Liyuan Huang, Zhenping Xie
Format: Article
Language:English
Published: Springer 2025-07-01
Series:Complex & Intelligent Systems
Subjects:
Online Access:https://doi.org/10.1007/s40747-025-02009-1
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