Transparent Contribution Evaluation for Secure Federated Learning ...

In this work, we propose a blockchain-based federated learning framework and a protocol to transparently evaluate each participant's contribution. Our framework ...

Transparent Contribution Evaluation for Secure. Federated Learning on Blockchain. Shuaicheng Ma. Emory University. Atlanta, US [email protected]. Yang Cao. Kyoto ...

Transparent Contribution Evaluation for Secure Federated Learning ...

Federated Learning is a promising machine learning paradigm when multiple parties collaborate to build a high-quality machine learning model.

Transparent Contribution Evaluation for Secure Federated Learning ...

In this work, we propose a blockchain-based federated learning framework and a protocol to transparently evaluate each participants' ...

Transparent Contribution Evaluation for Secure Federated Learning ...

PDF | On Apr 1, 2021, Shuaicheng Ma and others published Transparent Contribution Evaluation for Secure Federated Learning on Blockchain ...

Transparent Contribution Evaluation for Secure Federated Learning ...

Transparent Contribution Evaluation for Secure Federated Learning on Blockchain. https://doi.org/10.1109/icdew53142.2021.00023. Journal: 2021 IEEE 37th ...

2101.10572 - Transparent Contribution Evaluation for Secure ...

In this work, we propose a blockchain-based federated learning framework and a protocol to transparently evaluate each participant's contribution. Our framework ...

Contribution Evaluation in Federated Learning: Examining Current ...

[18] Shuaicheng Ma, Yang Cao, and Li Xiong. Transparent Contribution Evaluation for Secure. Federated Learning on Blockchain. arXiv:2101.10572 [cs], January ...

Transparent Contribution Evaluation for Secure Federated Learning ...

Transparent Contribution Evaluation for Secure Federated Learning on Blockchain. ブロックチェーン上のセキュアな連合学習のための透明な寄与評価【JST・京大機械 ...

Contributions Estimation in Federated Learning: A Comprehensive ...

Transparent contribution evaluation for secure federated learning on blockchain. In 2021 IEEE 37th International Conference on Data ...

‪Shuaicheng Ma‬ - ‪Google Scholar‬

Transparent contribution evaluation for secure federated learning on blockchain. S Ma, Y Cao, L Xiong. 2021 IEEE 37th international conference on data ...

Contribution Evaluation in Federated Learning - arXiv

[18] Shuaicheng Ma, Yang Cao, and Li Xiong. Transparent Contribution Evaluation for Secure. Federated Learning on Blockchain. arXiv:2101.10572 [ ...

Blockchain-Based Contribution Evaluation in Federated Learning

Abstract—Federated learning is a useful method for multiple organizations to share data while meeting privacy protection and data security requirements.

Contributions Estimation in Federated Learning: A Comprehensive ...

Efficient and Accurate Participant Contribution Evaluation in Federated Learning ... Transparent contribution evalua- tion for secure federated learning on ...

A Fair Contribution Measurement Method for Federated Learning

... security, enabling machine learning to occur in a ... In the current federated learning contribution evaluation schemes, evaluating ...

Secure Shapley Value for Cross-Silo Federated Learning

Each hospital provides a training set of its patient data for federated training and a test set for SV- based contribution evaluation. As shown in Figures 1a ...

[PDF] Secure Shapley Value for Cross-Silo Federated Learning ...

Transparent Contribution Evaluation for Secure Federated Learning on Blockchain · Shuaicheng MaYang CaoL. Xiong. Computer Science. 2021 IEEE 37th International ...

Achieving security and privacy in federated learning systems

We empirically evaluate security-enhancing methods in realistic federated learning scenarios. ... contribution from the previous global model. The ...

曹洋 (Yang Cao) - Transparent Contribution Evaluation for Secure ...

Transparent Contribution Evaluation for Secure Federated Learning on Blockchain. 37th IEEE International Conference on Data Engineering Workshops. Shuaicheng ...

Blockchain for federated learning toward secure distributed machine ...

Again, currently, FL systems do not have suitable and transparent contribution evaluation mechanisms and incentive mechanisms to ensure continuous active ...