A semi-synchronous federated learning framework with chaos-based encryption for enhanced security in medical image sharing

A semi-synchronous federated learning framework with chaos-based encryption for enhanced security in medical image sharing

Protecting sensitive health information and promoting clinical research depend on medical data security. This paper suggests an innovative framework that integrates healthcare engineering, chaotic encryption, and artificial intelligence (AI) to address the privacy issue of medical data. A novel semi...

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Bibliographic Details
Main Authors: Animesh Roy, Deva Raj Mahanta, Lipi B. Mahanta
Format: Article
Language:English
Published: Elsevier 2025-03-01
Series:Results in Engineering
Subjects:
Chaos-based encryption
Deep learning
Federated learning
Privacy-preserving
Medical cyber-physical systems (MCPS)
Online Access:http://www.sciencedirect.com/science/article/pii/S2590123024021297

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http://www.sciencedirect.com/science/article/pii/S2590123024021297

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