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Data desensitization method and device and readable storage medium

A data desensitization and desensitization technology, applied in the field of data processing, can solve the problems of poor data availability, time-consuming, high computational complexity, and achieve the effect of wide applicability

Pending Publication Date: 2021-04-09
NAT COMP NETWORK & INFORMATION SECURITY MANAGEMENT CENT
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

For example, some desensitization algorithms focus on data protection, but will lose some statistical characteristics, resulting in poor data availability, and are only suitable for scenarios with high data redundancy such as social data; some algorithms can take into account data protection and availability, but the calculation is complex High precision and time-consuming, only suitable for medical, financial and other scenarios that require high-precision data

Method used

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  • Data desensitization method and device and readable storage medium
  • Data desensitization method and device and readable storage medium
  • Data desensitization method and device and readable storage medium

Examples

Experimental program
Comparison scheme
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Embodiment 2

[0072] The second embodiment of the present invention provides a data desensitization device, such as figure 2 shown, including:

[0073] A sensitive data labeling module, configured to label the sensitive data in the data file through a pre-trained labeling model according to the obtained data file submitted by the user, so as to obtain the labeling file;

[0074] An evaluation module, configured to evaluate the desensitization algorithm matching the file type of the marked file by using preset evaluation rules;

[0075] The desensitization module is configured to desensitize the marked file according to the desensitization algorithm selected by the user from the evaluation results.

[0076] In this embodiment, the evaluation module can be integrated into the sensitive data labeling module, such as image 3 As shown, it includes sample data selection, pre-desensitization, pre-desensitization effect evaluation, desensitization algorithm determination, and final desensitizat...

Embodiment 3

[0080] The third embodiment of the present invention proposes an implementation case of a data desensitization method, such as Figure 4 As shown, this example takes the data desensitization of a bank's customer loan information as an example, including the following steps:

[0081] Step 1: Obtain the loan information of a bank customer submitted by the user. For example, the submitted information is an EXCEL form, including name, gender, ID number, place of origin, loan amount, loan date, and contact information. Determine the application scenario as the financial industry Scenes.

[0082] Step 2: According to the financial industry scenario, mark non-sensitive data as gender, place of origin, loan amount, and loan date, and sensitive data as name, ID number, and contact information, and then grade the marked sensitive data, such as 3, 9, and 9 respectively .

[0083] Step 3: Randomly sample data at a ratio of 15%, judge it as text content, and use 8 built-in types (K anony...

Embodiment 4

[0088] The fourth embodiment of the present invention proposes an implementation case of a data desensitization method, such as Figure 5 As shown, this example illustrates the data desensitization of social network pictures for analyzing personal preferences as an example, including the following steps:

[0089] Step 1: Obtain the collection of social network pictures submitted by users. The submitted information is a folder containing multiple jpg files. The content of the pictures covers faces, landscapes, animals, food, cars, and social industry scenes are selected.

[0090] Step 2: Label non-sensitive data as scenery, animals, food, and cars according to social industry scenarios, and sensitive data as faces, and their sensitivity levels are 9 respectively.

[0091] Step 3: Randomly sample sample data at a ratio of 10%, judge it as the content of the picture, and realize the pre-desensitization operation through two built-in (face-changing and Gaussian blur) algorithms fo...

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Abstract

The invention discloses a data desensitization method and device and a readable storage medium, and the method comprises the steps: marking sensitive data in a data file through a pre-trained marking model according to the obtained data file submitted by a user, so as to obtain a marking file; evaluating a desensitization algorithm matched with the file type of the annotation file by utilizing a preset evaluation rule; and completing desensitization of the annotation file according to a desensitization algorithm selected by the user from the evaluation result. According to the method, the desensitization algorithm matched with the file type of the annotation file is evaluated by utilizing the preset evaluation rule; according to the desensitization algorithm selected by the user from the evaluation result, desensitization of the annotation file is completed, so the corresponding desensitization algorithm can be determined through rule evaluation and user selection, and the method has wide applicability.

Description

technical field [0001] The invention relates to the technical field of data processing, in particular to a data desensitization method and a device-readable storage medium. Background technique [0002] In the current era of big data, various data analysis application technologies have been widely used in various aspects such as national governance, business operations, and personal daily life. Data has become the most popular basic resource nowadays, so the degree of attention to data security is also rising. , has become a topic of considerable attention. Data desensitization is to change the value while preserving the original characteristics of the data. It can maintain the security of the data while retaining the validity of the data, realize the reliable protection of sensitive private data, and avoid the risk of data leakage, so that it can be used in development and testing. Safely use masked real datasets in non-production and non-trusted environments. [0003] Fo...

Claims

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Application Information

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IPC IPC(8): G06F21/62G06F21/60G06N20/00G06F16/25
CPCG06F21/6245G06F21/602G06N20/00G06F16/252
Inventor 佟玲玲任博雅李鹏霄段东圣杜翠兰李扬曦段运强项菲井雅琪
Owner NAT COMP NETWORK & INFORMATION SECURITY MANAGEMENT CENT
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