Unsupervised joint modeling method based on ARM architecture chip

Abstract

The embodiment of the invention provides an unsupervised joint modeling method based on an ARM architecture chip. The method comprises the steps of providing a trusted execution environment based on an ARM architecture chip, a distributed unsupervised machine learning framework and a privacy computing interconnection system, wherein the trusted execution environment based on the ARM architecture chip comprises a plurality of servers based on the ARM architecture chip, one server serves as a service party, and the other servers serve as computing parties; realizing local data-based unsupervised model training of multiple computing parties locally, interacting with a parameter service party, realizing multi-party local model security aggregation, and constructing a global model; and enabling the service party and each computing party to perform data transmission and model parameter aggregation through a privacy computing interconnection system constructed based on MPC, a trusted execution environment and an encrypted connection mode, so that the privacy of related data is ensured. While privacy data of all parties are protected, multi-party data joint modeling is realized, and multi-party data islands are broken through.

Description

technical field [0001] The present invention relates to the field of computer technology, and more specifically, relates to a non-supervised joint modeling method based on an ARM architecture chip. Background technique [0002] At present, the large amount of data accumulated in various industries requires multi-party data joint for risk control and marketing in order to better mine the value of data. [0003] The way to achieve multi-party data union in the prior art usually includes: 1) summarizing the data of each participant, then performing model training and jointly applying the model; 2) storing the data of each participant in a third party; 3) each Participants realize data sharing through a customized data circulation platform, and each participant agrees on an interface with each other, and calls the corresponding data through the interface. [0004] However, no matter which method is used, there will be a risk of data leakage or the modeling process cannot verify...

AI Technical Summary

Problems solved by technology

[0004] However, no matter which method is used, there will be a risk of data leakage or the modeling process cannot be verified and audited, which is very likely to cause major losses to all participants, and may also reduce the trust between the participants.

Moreover, the existing data modeling methods have high customization costs, cumbersome processes, and insufficient transparency

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