연구 분야: Verification
학회: International Journal of Information Technology
In the rapidly evolving landscape of the Industrial Internet of Things (IIoT) within smart cities, ensuring data security, confidentiality, and privacy remains a significant challenge. Decentralized Federated Learning (DFL) and Hyperledger Fabric (HF) based distributed databases ensure the confidentiality and privacy of data. We propose an innovative framework to fortify smart applications, aligned with the principles of IIoT. The proposed approach leverages the integration of the Elliptic Curve Digital Signature Algorithm (ECDSA) for data verification and the augmentation of DFL to bolster security measures. Our method uses ECDSA’s cryptographic power for safe data authentication and integrity checks in the context of smart city ecosystems. With the help of DFL, we do privacy and confidentiality-preserving collaborative model training. The integration of the HF blockchain framework further strengthens the resilience of the proposed framework. Our proposed approach outperforms existing models in terms of secure data transfer for IIoT devices, making it a robust solution for Industry 5.0 and the future of smart city development.
| 발행 연도 | 2024년 |
|---|---|
| 인용수 | 0 |
| 출판 국가 | Andorra |
| 사이트 | Springer |
| 좋아요 수 | 0 |