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An analysis method and device for a data privacy protection protocol

A data privacy and analysis method technology, applied in the computer field, can solve problems such as high labor costs, low efficiency, and difficulty in updating data privacy protection projects, and achieve the effect of reducing the difficulty of updating and improving analysis efficiency

Active Publication Date: 2021-08-17
BEIJING REALAI TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] However, in the federated learning framework FATE and its variants, the data privacy protection protocol needs to be derived by manual analysis and calculation formulas. This manual analysis method is not only high in labor costs and low in efficiency; more importantly, when changes to algorithms such as linear regression ( For example, when adding or deleting regular items, etc.), the calculation formula must be re-analyzed to determine whether the data meets the requirements of data privacy protection, which makes it difficult to make targeted updates for a large number of data privacy protection projects
It can be seen that the manual analysis method for data privacy protection agreements has the problems of high cost, low efficiency and difficulty in updating data privacy protection projects

Method used

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  • An analysis method and device for a data privacy protection protocol
  • An analysis method and device for a data privacy protection protocol
  • An analysis method and device for a data privacy protection protocol

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0031] refer to figure 1 The flow chart of the analysis method of the data privacy protection agreement shown, the method mainly includes the following steps:

[0032] Step S102, acquiring the program code of the linear regression algorithm.

[0033] In practical applications, the program code used to train the linear regression algorithm needs to be executed by two different participants, and the program codes executed by different participants are different. Regression Algorithm Training. According to the participants, the program code can be divided into X data and Y data. The X data represents the part of the program code executed by the participant on the X side, and the Y data represents the part of the program code executed by the participant on the Y side. In this embodiment, the obtained program code of the linear regression algorithm is a complete program code including both X data and Y data.

[0034] Step S104, converting the program code based on the data flow ...

Embodiment 2

[0062] This embodiment provides an analysis device for a data privacy protection protocol, which is used to implement the analysis method for a data privacy protection protocol provided in the embodiment. refer to Figure 5 , the device consists of:

[0063] An acquisition module 502, configured to acquire the program code of the linear regression algorithm;

[0064] The conversion module 504 is used to convert the program code based on the data flow graph generation tool to obtain a data flow graph corresponding to the linear regression algorithm; wherein, the data flow graph includes a series of operators;

[0065] A judging module 506, configured to judge whether the current operator satisfies a preset data leakage condition for any operator in the data flow diagram;

[0066] The determination module 508 is configured to determine that the operator has a risk of data leakage and determine that the program code does not meet the data privacy protection agreement if it is s...

Embodiment 3

[0073] An embodiment of the present invention provides an electronic device, which includes: a processor and a storage device; a computer program is stored on the storage device, and the computer program executes the analysis of the data privacy protection protocol as described in Embodiment 1 when the computer program is run by the processor method.

[0074]An embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored. When the computer program is run by a processor, the steps of the method for analyzing the data privacy protection protocol in the first embodiment above are executed.

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Abstract

The disclosure provides an analysis method and device for a data privacy protection protocol, which relates to the field of computer technology. The method includes: obtaining the program code of the linear regression algorithm; converting the program code based on a data flow graph generation tool to obtain the corresponding linear regression algorithm Data flow graph; wherein, the data flow graph includes a series of operators; for any operator in the data flow graph, it is judged whether the current operator satisfies the preset data leakage conditions; if so, it is determined that the operator has a risk of data leakage , and determine that the program code does not meet the data privacy protection agreement. The disclosure can improve the analysis efficiency of the data privacy protection protocol and reduce the update difficulty of the data privacy protection project.

Description

technical field [0001] The present disclosure relates to the field of computer technology, in particular to an analysis method and device for a data privacy protection protocol. Background technique [0002] Data privacy protection generally means that the characteristics or labels of the place where the data belongs (the party with permission) cannot be transmitted in plain text to the place where the data does not belong (the party without permission). It not only requires multi-party data to participate in information interaction to complete model training, but also needs to ensure data security and protect data privacy. The main technology for data privacy protection in current machine learning scenarios is federated learning (also known as shared learning). [0003] However, in the federated learning framework FATE and its variants, the data privacy protection protocol needs to be derived by manual analysis and calculation formulas. This manual analysis method not only...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F21/14
CPCG06F21/14
Inventor 徐世真王鲲鹏朱晓芳田天朱军
Owner BEIJING REALAI TECH CO LTD
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