A Multifaceted Survey on Federated Learning: Fundamentals, Paradigm Shifts, Practical Issues, Recent Developments, Partnerships, Trade-Offs, Trustworthiness, and Ways Forward

Federated learning (FL) is considered a de facto standard for privacy preservation in AI environments because it does not require data to be aggregated in some central place to train an AI model. Preserving data on the client side and sharing only the model’s parameters with a central server...

Ausführliche Beschreibung

Bibliografische Detailangaben

Hauptverfasser:	Abdul Majeed, Seong Oun Hwang
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	IEEE 2024-01-01
Schriftenreihe:	IEEE Access
Schlagworte:	Federated learning AI models poisoning attacks privacy preservation training data
Online-Zugang:	https://ieeexplore.ieee.org/document/10555253/
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