A Blockchain-Enabled Decentralized Federated Learning System with Transparent and Open Incentive and Audit Contracts
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-8101-4_18
Reference22 articles.
1. Awan, S., Li, F., Luo, B., Liu, M.: Poster: a reliable and accountable privacy-preserving federated learning framework using the blockchain. In: Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security, pp. 2561–2563 (2019)
2. Chen, Y., et al.: DIM-DS: dynamic incentive model for data sharing in federated learning based on smart contracts and evolutionary game theory. IEEE Internet Things J. 9(23), 24572–24584 (2022). https://doi.org/10.1109/JIOT.2022.3191671
3. Dai, H.N., Zheng, Z., Zhang, Y.: Blockchain for internet of things: a survey. IEEE Internet Things J. 6(5), 8076–8094 (2019)
4. Gao, L., Li, L., Chen, Y., Xu, C., Xu, M.: FGFL: a blockchain-based fair incentive governor for federated learning. J. Parallel Distrib. Comput. 163, 283–299 (2022). https://doi.org/10.1016/j.jpdc.2022.01.019
5. Hard, A., et al.: Federated learning for mobile keyboard prediction. arXiv preprint arXiv:1811.03604 (2018)
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