Trustworthiness Assurance for Model Updates in Federated Learning

<p>Training accurate Machine Learning (ML) models requires access to large volumes of data, often personal or confidential, raising significant privacy concerns under certain rules and regulations. Traditional protection methods, such as data encryption, are effective in protecting data content but...

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Detalles Bibliográficos

Autores principales:	Ermis, Orhan, Khadraoui, Djamel
Formato:	Capítulo de libro
Lenguaje:	inglés
Publicado:	IntechOpen 2026
Materias:	Physical Sciences, Engineering and Technology
Acceso en línea:	https://www.intechopen.com/chapters/1235771
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