Federal learning security aggregation method and apparatus, and electronic device

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...

AI Technical Summary

Problems solved by technology

[0004] This application provides a federated learning security aggregation method, device, and electronic equipment to solve the defects of the prior art that reduce the reliability of federated learning aggregation results, etc.

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