US 12,244,689 B2
Method and apparatus for vertical federated learning
Yong Cheng, Guangdong (CN); Fangcheng Fu, Guangdong (CN); Pin Xiao, Guangdong (CN); and Yangyu Tao, Guangdong (CN)
Assigned to TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED, Shenzhen (CN)
Filed by TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED, Guangdong (CN)
Filed on Sep. 30, 2022, as Appl. No. 17/957,740.
Application 17/957,740 is a continuation of application No. PCT/CN2021/118259, filed on Sep. 14, 2021.
Claims priority of application No. 202011064959.3 (CN), filed on Sep. 30, 2020.
Prior Publication US 2023/0028606 A1, Jan. 26, 2023
Int. Cl. H04L 9/08 (2006.01); G06N 20/20 (2019.01); H04L 9/00 (2022.01); H04L 9/14 (2006.01); H04L 9/30 (2006.01)
CPC H04L 9/0819 (2013.01) [G06N 20/20 (2019.01); H04L 9/008 (2013.01); H04L 9/0869 (2013.01); H04L 9/14 (2013.01); H04L 9/30 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method for vertical federated learning, applied to an upper-layer participation node in multiple participation nodes deployed in a multi-way tree topology, the upper-layer participation node corresponding to k lower-layer participation nodes, a submodel in a federated model being locally deployed in each participation node, k being an integer greater than 1, the method comprising:
distributing a first public key corresponding to the upper-layer participation node to the k lower-layer participation nodes, and acquiring k second public keys corresponding to the k lower-layer participation nodes respectively;
performing, by the upper-layer participation node, secure two-party joint computation with the k lower-layer participation nodes respectively with the first public key and the k second public keys as encryption parameters, to obtain k two-party joint outputs of the federated model, the secure two-party joint computation comprising forward computation for the submodel performed, in a manner of homomorphic encryption, by the upper-layer participation node and a lower-layer participation node jointly using respective data of the upper-layer participation node and the lower-layer participation node; and
aggregating the k two-party joint outputs to obtain a multi-party joint output corresponding to the upper-layer participation node and the k lower-layer participation nodes;
wherein the upper-layer participation node is a lower-layer participation node of a higher-layer participation node in the multi-way tree topology, and the method further comprises:
acquiring a third public key corresponding to the higher-layer participation node; and
performing, by the upper-layer participation node as a lower-layer participation node, secure two-party joint computation with the higher-layer participation node with the first public key and the third public key as encryption parameters, to obtain a two-party joint output of the federated model.