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Federated Learning in Edge Computing: Vulnerabilities, Attacks, and Defenses—A Survey

Federated Learning (FL), a distributed machine learning framework, enables collaborative model training across multiple devices without sharing raw data, thereby preserving privacy and reducing communication costs. When combined with Edge Computing (EC), FL brings computations closer to data sources...

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Principais autores: Sahar Alhawas, Murad A. Rassam
Format: Artigo
Sprog:Inglês
Udgivet: MDPI AG 2026-02-01
Serier:Sensors
Fag:
federated learning
edge computing
security
privacy
vulnerabilities
adversarial attacks
Online adgang:https://www.mdpi.com/1424-8220/26/4/1275
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