Development of Federated Blockchain-IoT Public Health Network with Privacy-Preserving Analytics
Keywords:
Federated Learning, Blockchain, IoT Healthcare, Privacy Preservation, Cross-Chain Interoperability, Epidemic Response, Secure Aggregation, Sharding, Network SecurityAbstract
The rapid expansion of Internet of Things (IoT) devices in healthcare has caused concerns around data privacy, interoperability, and system scalability. Conventional centralized data processing models expose sensitive patient information to security vulnerabilities and hinder collaborative analytics across healthcare institutions. To address these challenges, this paper proposes a novel Federated Blockchain-IoT Public Health Network that combines privacy-preserving federated learning with permissioned blockchain technology and cross-chain atomic swap protocols. This integration enables secure, efficient, and interoperable healthcare data analytics in a distributed environment. The framework employs homomorphic encryption and secure aggregation to protect patient data privacy while allowing collaborative model training on decentralized healthcare nodes
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Articles in this journal are licensed under the Creative Commons Attribution-NonCommercial 4.0 International License. This license permits others to copy, distribute, and adapt the work, provided it is for non-commercial purposes, and the original author and source are properly credited.
