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Patent Searching and Data


Title:
BLOCKCHAIN-BASED FEDERATED LEARNING METHOD AND APPARATUS
Document Type and Number:
WIPO Patent Application WO/2022/217914
Kind Code:
A1
Abstract:
A blockchain-based federated learning method and apparatus. The method comprises: a first node trains an ith-round local model on the basis of local training data to determine gradient information of the trained (i+1)th-round local model (202), respectively clips and quantizes each piece of first sub-gradient information in the gradient information of the (i+1)th-round local model on the basis of gradient clipping and quantization rules to obtain each piece of second sub-gradient information (203), merges every m pieces of second sub-gradient information among all pieces of second sub-gradient information according to a gradient merging rule to obtain n types of third sub-gradient information (204), and performs homomorphic encryption on the n types of third sub-gradient information to obtain n types of ciphertexts (205), and sends the n types of ciphertexts to a blockchain (206). Because each piece of first sub-gradient information in the gradient information of the local model is respectively clipped, quantized and merged, and then homomorphic encryption is performed thereon, computing resource consumption generated by the homomorphic encryption can be reduced, and network resources consumed in the ciphertext transmission process can be reduced.

Inventors:
MIAO YINBIN (CN)
ZHENG WEI (CN)
TONG QIUYUN (CN)
MA ZHUORAN (CN)
FAN RUIBIN (CN)
ZHANG KAIXIANG (CN)
LI HUIZHONG (CN)
YAN QIANG (CN)
LI CHENGBO (CN)
Application Number:
PCT/CN2021/131317
Publication Date:
October 20, 2022
Filing Date:
November 17, 2021
Export Citation:
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Assignee:
WEBANK CO LTD (CN)
UNIV XIDIAN (CN)
International Classes:
G06F21/60; G06N20/20
Foreign References:
CN113095510A2021-07-09
CN112288097A2021-01-29
CN109951438A2019-06-28
CN112235384A2021-01-15
US20200380356A12020-12-03
CN111401552A2020-07-10
Attorney, Agent or Firm:
TDIP & PARTNERS (CN)
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