A model training method and a device based on shared data

A technology for model training and data sharing, applied in digital data protection, electrical digital data processing, computer security devices, etc.

Active Publication Date: 2019-02-05
ADVANCED NEW TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

This technology allows users to train their collaborative team with better accuracy through various types of interactions between different parties involved during collaboration sessions or when they want access protected resources like databases. By embedding sensitive data into an operating system's secure shelling layer called Trusted Execution Environment (TEE), these technologies help protect both inside and external sources from being compromised.

Problems solved by technology

The technical issue addressed in this patented text relates to improving the efficiency or safety of accessing shared datasets while also maintaining user privacy rights during collaborative work between different parties involved.

Method used

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  • A model training method and a device based on shared data
  • A model training method and a device based on shared data
  • A model training method and a device based on shared data

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Embodiment approach

[0163] The above describes the model training scheme based on shared data provided by the embodiments of this specification as a whole. In combination with actual application requirements, there are some alternative implementation methods in terms of detailed overall design. Examples are as follows:

[0164] In S101 to S102, only one piece of data can be read to the trusted execution environment at a time, or multiple pieces of data can be read to the trusted execution environment at a time. That is, in each iteration process, N pieces of ciphertext data are obtained from each data provider, where N can be a preset value not less than 1, and the replacement of training samples is achieved by obtaining different data each time.

[0165] In addition, it can be understood that the acquisition of training sample data can be acquired successively with the iterative process, or acquired at a time. For example, if the number of data required for each iteration is N, it can either obtain N...

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Abstract

A model training method and apparatus based on shared data are disclosed. On the one hand, joint training can be carried out according to the data provided by multiple data providers, so as to obtaina more accurate and comprehensive data model; On the other hand, the operations (such as data decryption operation, local model parameter update operation, etc.) involved in the privacy data during model training are encapsulated in a trusted execution environment of the data provider. Data plaintext cannot be acquired outside the trusted execution environment.

Description

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Claims

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Application Information

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Owner ADVANCED NEW TECH CO LTD
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