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Privacy disclosure risk assessment method, device and system based on data open sharing

A technology for privacy leakage and risk assessment, applied in the field of data sharing, which can solve the problems of low desensitization, loss of data utility, and impact of data utility.

Active Publication Date: 2022-03-08
GUIZHOU UNIVERSITY OF FINANCE AND ECONOMICS
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] Before the data is openly shared, privacy protection processing such as desensitization is often performed on the data to protect the privacy of personal information. Impact
For example, the desensitization degree is low, the data utility is high, but it is easy to leak personal information and other privacy; the desensitization degree is high, the privacy is not easy to leak, but it will cause the loss of data utility
[0003] At present, there is no reliable reference standard for the control of desensitization degree, so as to control the degree of desensitization through this reference standard, so that the risk of privacy leakage can be controlled within an acceptable range, and the security after desensitization can be guaranteed. of data has some data utility

Method used

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  • Privacy disclosure risk assessment method, device and system based on data open sharing
  • Privacy disclosure risk assessment method, device and system based on data open sharing
  • Privacy disclosure risk assessment method, device and system based on data open sharing

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0061] see figure 1 , figure 1 It is a schematic flow chart of a privacy leakage risk assessment method based on open data sharing provided by Embodiment 1 of the present application.

[0062] Such as figure 1 As shown, the privacy leakage risk assessment method based on open data sharing provided in this embodiment includes:

[0063] Step 11. Obtain the user's first data set, second data set, third data set, and fourth data set; the first data is the original data set to be released or the original data set to be shared; the second data set is the data set to be released or the dataset to be shared; the third dataset is the original dataset that has been opened or the original dataset that has been shared; the fourth dataset is the dataset that has been opened or the dataset that has been shared.

[0064] Step 12. According to the first data set and the third data set, an associated original data set of each data in the first data set is obtained. There are many ways to j...

Embodiment 2

[0092] see figure 2 , figure 2 It is a schematic structural diagram of a privacy leakage risk assessment device based on data open sharing provided in Embodiment 2 of the present application.

[0093] Such as figure 2 As shown, the privacy leakage risk assessment device based on open data sharing provided by this embodiment includes:

[0094] The first acquisition module 21 is used to acquire the user's first data set, second data set, third data set, and fourth data set; the first data is the original data set to be opened or the original data set to be shared; the second data set Data set to be opened or shared; the third data set is the original data set that has been opened or the original data set that has been shared; the fourth data set is the data set that has been opened or shared;

[0095] The first association module 22 is configured to obtain an associated original data set of each data in the first data set according to the first data set and the third data ...

Embodiment 3

[0111] see image 3 , image 3 It is a schematic structural diagram of a privacy leakage risk assessment system based on data open sharing provided in Embodiment 3 of the present application.

[0112] Such as image 3 As shown, the privacy leakage risk assessment system based on open data sharing provided by this embodiment includes:

[0113] Privacy leakage risk assessment module 31;

[0114] The privacy leakage risk assessment module includes a processor 311, and a memory 312 connected to the processor;

[0115] The memory is used to store a computer program, and the computer program is at least used to execute the privacy leakage risk assessment method based on open data sharing as in Embodiment 1;

[0116] The processor is used to call and execute the computer program in the memory.

[0117] In addition, the system can also include:

[0118] The user data resource pool 32 is used to store the first data set, the second data set, the third data set, and the fourth dat...

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Abstract

This application relates to a privacy leakage risk assessment method, device and system based on open data sharing, including: obtaining the first data set, the second data set, the third data set, and the fourth data set; according to the first data set and The third data set obtains the associated original data set; according to the associated original data set and the fourth data set, the associated open data set corresponding to the associated original data set is obtained; according to the difference between the associated original data set and the associated open data set, the second The privacy information of each data in the data set is obtained to obtain the first restored data set; the similarity between the first data set and the data in the first restored data set is calculated to obtain the first similarity set; the direct privacy leakage risk is obtained according to the first similarity set value. Taking the risk value of direct privacy leakage as a reference standard for the control of desensitization degree can accurately control the risk of privacy leakage within an acceptable range, while ensuring that the data has a certain data utility.

Description

technical field [0001] The present application relates to the technical field of data sharing, and in particular to a privacy leakage risk assessment method, device and system based on data open sharing. Background technique [0002] Before the data is openly shared, privacy protection such as desensitization is often performed on the data to protect the privacy of personal information. Impact. For example, if the desensitization degree is low, the data utility is high, but it is easy to leak personal information and other privacy; if the desensitization degree is high, the privacy is not easy to leak, but it will cause the loss of data utility. [0003] At present, there is no reliable reference standard for the control of desensitization degree, so as to control the degree of desensitization through this reference standard, so that the risk of privacy leakage can be controlled within an acceptable range, and the security after desensitization can be guaranteed. The data ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F21/62
CPCG06F21/6245
Inventor 丁红发彭长根田有亮
Owner GUIZHOU UNIVERSITY OF FINANCE AND ECONOMICS