Enhancing Healthcare Cybersecurity Using Federated Learning and Blockchain

Prof. Rakesh Kumar

Abstract


This study proposes a novel approach that combines federated learning and blockchain to enhance cybersecurity in healthcare networks. Federated learning allows decentralized training of machine learning models on sensitive patient data, preserving privacy. Blockchain ensures secure model updates and prevents tampering during transmission. The system is tested in scenarios involving multiple healthcare providers, demonstrating improved detection rates of cyber threats while maintaining data confidentiality. The research offers a scalable and privacy-preserving solution for advancing cybersecurity in the healthcare sector.

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