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A Data Acquisition and Regression Analysis Method that Provides Privacy Protection

A technology of data collection and privacy protection, which is applied in the field of data processing, can solve problems such as privacy leakage, and achieve the effect of reducing complexity and bias estimation

Active Publication Date: 2022-05-31
NANJING UNIV OF POSTS & TELECOMM
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] If data is held by individuals, there must be a privacy breach for them

Method used

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  • A Data Acquisition and Regression Analysis Method that Provides Privacy Protection
  • A Data Acquisition and Regression Analysis Method that Provides Privacy Protection

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Embodiment Construction

[0025] The present invention will be further described below in conjunction with the accompanying drawings.

[0030] Step 1-1: Assume that the data provider i∈[n], i={1,2,...n} holds the inherent attribute feature vector x

[0033] Step 1-2-2: Expand the above-mentioned loss function into a polynomial form about θ. It can be seen from the above that θ is a d

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PUM

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Abstract

The invention discloses a data collection and regression analysis method providing privacy protection, adopts differential privacy to protect the privacy of data providers, and encourages providers to provide real data through a compensation mechanism. First, in the analysis module of the regression model, this method adopts the ridge regression model, expands the loss function into a form of polynomial chaos, and adds Laplace noise to the coefficients in front of each polynomial, so as to ensure that the regression model obtained by training is both The privacy of the data provider is protected, and the accuracy of the model is guaranteed; then, in the remuneration payment module, the regression model obtained by removing the data provided by the data provider is calculated, compared with the overall regression model, and the above two The error is used as a measure of the remuneration of each data provider, in other words, the smaller the error, that is, the more accurate the data, the more the corresponding reward. In short, through privacy protection and appropriate rewards, this method can incentivize more realistic reporting data and train more accurate models.

Description

A data collection and regression analysis method that provides privacy protection technical field The present invention relates to a kind of data collection and regression analysis method that provide privacy protection, belong to the field of data processing technology area. Background technique [0002] At present, fitting a linear model may be the most basic and most basic learning task, with applications ranging from statistics to medicine. and sociology applications. In many cases, the data from which regression learning was performed to obtain a model was not It is in the hands of the analyst performing the regression task and must be obtained from the individual. These scenarios apparently include medical trials and population censuses , as well as mining online behavioral data, a practice that is happening on a large scale today. [0003] If data is held by individuals, there must be a privacy breach for them. to motivate them Provide your own information ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F21/62G16H50/70G06Q10/04G06Q10/10
CPCG06F21/6245G06Q10/04G06Q10/1057G16H50/70
Inventor 王玉峰顾敏
Owner NANJING UNIV OF POSTS & TELECOMM
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