典型文献
Blockchain-Based Architectural Framework for Vertical Federated Learning
文献摘要：
The introduction of blockchain to federated learning (FL) is a promising solution to enable anonymous clients to collaboratively learn a shared prediction model using local data while avoiding the risk caused by the central server. However, the current researches only apply a shallow convergence between the two technologies. The aroused problems, such as the unsuitable consensus, the lack of incentive mechanism, and the incompetence of handling vertically partitioned data, make the blockchain-based FL exist in name only. This paper puts forward a novel blockchain-based framework for vertical FL with a specified consensus and incentive. Moreover, a real-world example is demonstrated to prove the practicability of our work.
文献关键词：
中图分类号：
作者姓名：
QIAN Chen;ZHU Wenjing
作者机构：
School of Computer Science and Technology,Donghua University,Shanghai 201620,China;Institute of Scientific and Technical Information of Shanghai,Shanghai Library,Shanghai 200031,China
文献出处：
引用格式：
[1]QIAN Chen;ZHU Wenjing-.Blockchain-Based Architectural Framework for Vertical Federated Learning)[J].东华大学学报（英文版）,2022(03):211-219
A类：
B类：
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AB值：
0.741337
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