A Survey on Securing Federated Learning: Analysis of Applications, Attacks, Challenges, and Trends

A Survey on Securing Federated Learning: Analysis of Applications, Attacks, Challenges, and Trends

The growth of data generation capabilities, facilitated by advancements in communication and computation technologies, as well as the rise of the Internet of Things (IoT), results in vast amounts of data that significantly enhance the performance of machine learning models. However, collecting all n...

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Bibliographic Details
Main Authors: Helio N. Cunha Neto, Jernej Hribar, Ivana Dusparic, Diogo Menezes Ferrazani Mattos, Natalia C. Fernandes
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Federated learning
machine learning
collaborative learning
information security
multiaccess edge computing
Online Access:https://ieeexplore.ieee.org/document/10107622/

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