Privacy-Preserving Federated Learning with Galois Automorphism-Driven Linear Transformation with Brakerski-Fan-Vercauteren for Medical Data

Healthcare data is frequently fragmented over diverse organizations because of its extremely complex and confidential nature. However, the existing Federated Learning (FL) approach through a central server creates various challenges within healthcare, such as privacy vulnerabilities and regulatory c...

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Autors principals:	Kavitha C. R., Sowmya K. N.
Format:	Artigo
Idioma:	Inglês
Publicat:	Sciendo 2026-06-01
Col·lecció:	Cybernetics and Information Technologies
Matèries:	brakerski-fan-vercauteren federated learning fully homomorphic encryption (fhe) galois automorphism-driven linear transformation and xceptionnet
Accés en línia:	https://doi.org/10.2478/cait-2026-0012
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