Privacy-Preserving Federated Learning Using Homomorphic Encryption

Federated learning (FL) is a machine learning technique that enables distributed devices to train a learning model collaboratively without sharing their local data. FL-based systems can achieve much stronger privacy preservation since the distributed devices deliver only local model parameters train...

Descripció completa

Dades bibliogràfiques

Autors principals:	Jaehyoung Park, Hyuk Lim
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2022-01-01
Col·lecció:	Applied Sciences
Matèries:	privacy preserving homomorphic encryption federated learning
Accés en línia:	https://www.mdpi.com/2076-3417/12/2/734
Etiquetes:	Afegir etiqueta Sense etiquetes, Sigues el primer a etiquetar aquest registre!