The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Sep. 16, 2025

Filed:

Apr. 18, 2022
Applicants:

The Governing Council of the University of Toronto, Toronto, CA;

Hitachi Solutions, Ltd., Tokyo, JP;

Inventors:

Ashish Khisti, Ontario, CA;

Seyederfan Hosseini, Ontario, CA;

Mitsuharu Oba, Tokyo, JP;

Takushi Fujimoto, Tokyo, JP;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04L 9/08 (2006.01); G06N 20/00 (2019.01); H04L 9/00 (2022.01); H04L 9/30 (2006.01);
U.S. Cl.
CPC ...
H04L 9/088 (2013.01); G06N 20/00 (2019.01); H04L 9/008 (2013.01); H04L 9/085 (2013.01); H04L 9/30 (2013.01);
Abstract

It is provided a federated learning system for aggregating gradient information representing a result of training an AI model in an edge device, the federated learning system comprising the edge device and a server apparatus, the training module in the edge device being configured to generate an edge switch share in which the encrypted aggregated gradient is encrypted, and to transmit the generated edge switch share to the server apparatus, the encryption/decryption module in the server apparatus being configured to generate an encrypted aggregated gradient for decryption by adding edge switch shares received from the plurality of the edge device, generate an aggregated gradient by decrypting the generated encrypted aggregated gradient for decryption, and to transmit the generated aggregated gradient to the edge device, the training module in the edge device being configured to train the AI model by using the aggregated gradient received from the server apparatus.


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