Federal learning security aggregation method and apparatus, and electronic device

A security aggregation and federation technology, applied in the field of network security, can solve problems such as reducing the reliability of federated learning aggregation results, and achieve the effect of improving reliability

Pending Publication Date: 2022-01-11
国网智能电网研究院有限公司南京分公司 +4
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] This application provides a federated learning security aggregation method, device, and electronic equipmen

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  • Federal learning security aggregation method and apparatus, and electronic device
  • Federal learning security aggregation method and apparatus, and electronic device
  • Federal learning security aggregation method and apparatus, and electronic device

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Embodiment Construction

[0066] In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments It is a part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of this application.

[0067] In addition, the terms "first", "second", etc. are used for descriptive purposes only, and should not be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. In the descriptions of the following embodiments, "plurality" means two or more, unless otherwise specifically define...

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Abstract

The invention provides a federated learning security aggregation method and device and electronic equipment. The method comprises the following steps: acquiring model parameter update information of all users participating in federated learning for a current sample category; according to the model parameter updating information, performing model parameter updating on a preset global model to obtain a new global model corresponding to each user; extracting a test sample corresponding to the current sample category from a preset test set, and inputting the test sample into the new global model to obtain a neuron average activation value corresponding to each new global model; determining a user clustering result according to the neuron average activation value corresponding to each new global model; and according to a user clustering result, determining malicious users currently participating in federal learning. The malicious user is determined according to the model neuron activation conditions of different users for a certain sample category, so that the authentication of the federated learning participating user identity is realized, and the reliability of a federated learning aggregation result is improved.

Description

technical field [0001] The present application relates to the technical field of network security, in particular to a federated learning security aggregation method, device and electronic equipment. Background technique [0002] Federated learning can solve the problem of Android mobile phone users updating models locally. The goal of federated learning is to achieve joint modeling and improve the effect of models on the basis of ensuring data privacy, security and legal compliance. Its essence is a distributed machine learning techniques. [0003] However, in practical applications, malicious users may steal a certain type of training data from other users through GAN attacks, which reduces the reliability of federated learning aggregation results. Contents of the invention [0004] The present application provides a federated learning security aggregation method, device and electronic equipment to solve the defects of the prior art, such as lowering the reliability of f...

Claims

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Application Information

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IPC IPC(8): G06N20/20G06K9/62G06N3/06G06N3/08
CPCG06N20/20G06N3/061G06N3/08G06F18/22G06F18/23
Inventor 石聪聪黄秀丽何维民夏雨潇高先周华景煜
Owner 国网智能电网研究院有限公司南京分公司
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