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Hierarchical Privacy Preservation Method in Hierarchical Data Publishing

A technology of hierarchical data and privacy protection, applied in the field of privacy protection, it can solve problems such as hierarchical data publishing attacks, and achieve the effect of enhancing the strength of privacy protection and solving the problem of adjacent attacks.

Active Publication Date: 2020-11-10
GUANGXI NORMAL UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] What the present invention aims to solve is the problem of proximity attack on the release of hierarchical data in the existing hierarchical data release technology, and provides a hierarchical privacy protection method in the release of hierarchical data

Method used

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  • Hierarchical Privacy Preservation Method in Hierarchical Data Publishing
  • Hierarchical Privacy Preservation Method in Hierarchical Data Publishing
  • Hierarchical Privacy Preservation Method in Hierarchical Data Publishing

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Embodiment Construction

[0032] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in combination with specific examples and with reference to the accompanying drawings.

[0033] First, explain the data model of hierarchical data data:

[0034] (1) Each piece of hierarchical data has a common construction scheme, such as figure 1 shown;

[0035] (2) Each piece of hierarchical data has an acyclic tree structure with a root node;

[0036] (3) Each node in the hierarchical data can have multiple quasi-identifier attributes QI, and each node has at most one sensitive attribute SA, all quasi-identifier attribute values ​​of the node are used as the node label, and the sensitive attribute The value is used as additional information of the node.

[0037] A hierarchical privacy protection method in hierarchical data release, which specifically includes the following steps:

[0038] Step 1. Classif...

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PUM

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Abstract

The invention discloses a hierarchical privacy protection method in the release of hierarchical data. First, the sensitive attributes of the original hierarchical data are classified according to the actual sensitivity, and then the frequency parameter α is set according to the divided grades. i To limit the frequency of different levels of sensitive attributes in the equivalence class, and then use the clustering method to achieve a given privacy model. The present invention well solves the problem of privacy leakage caused by the proximity attack on the sensitive attributes of the existing hierarchical data publishing technology, improves the protection of hierarchical data privacy, and enhances the security of data; the present invention is for The protection of hierarchical data has certain practical significance and practical value.

Description

technical field [0001] The invention relates to the technical field of privacy protection, in particular to a hierarchical privacy protection method in hierarchical data publishing. Background technique [0002] Human beings have entered the information age in the 21st century, and the information field is developing very rapidly. As the Internet continues to penetrate into various fields such as politics, economy, culture, medical care, and education, and generates a large amount of data, these data often need to be shared with untrusted third parties for research purposes, resulting in privacy disclosure of personal information. The problem is getting more and more attention. At the same time, privacy-preserving data distribution technology (PPDP) has been extensively researched and developed, but these technologies are mainly aimed at relational data. For example, the k-anonymity and L-diversity models of classic relational data. However, the current data often has a c...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F21/62G06K9/62
CPCG06F21/6245G06F18/2321
Inventor 王金艳蔡国庆李先贤
Owner GUANGXI NORMAL UNIV
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