WFB: watermarking-based copyright protection framework for federated learning model via blockchain
Author:
Funder
National Key R &D Program of China
Publisher
Springer Science and Business Media LLC
Link
https://www.nature.com/articles/s41598-024-70025-1.pdf
Reference28 articles.
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2. Reddy, K. D., Reddy, T. & Reddy, T. A comprehensive survey on federated learning techniques for healthcare informatics. Computat. Intell. Neurosci. 2023, 8393990 (2023).
3. Aouedi, O., Sacco, A., Piamrat, K. & Marchetto, G. Handling privacy-sensitive medical data with federated learning: Challenges and future directions. IEEE J. Biomed. Health Inform. 27, 790–803 (2022).
4. Ali, M., Naeem, F., Tariq, M. A. & Kaddoum, G. Federated learning for privacy preservation in smart healthcare systems: A comprehensive survey. IEEE J. Biomed. Health Inform. 27, 778–789 (2022).
5. Ding, N., Fang, Z. & Huang, J. Optimal contract design for efficient federated learning with multi-dimensional private information. IEEE J. Sel. Areas Commun. 39, 186–200 (2021).
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