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Graph data publishing privacy protection cluster anonymity method and system

A technology of privacy protection and graph data, which is applied in the direction of digital transmission system, transmission system, data exchange network, etc., can solve the problems of general limitation and achieve the effect of ensuring privacy and security

Inactive Publication Date: 2018-12-14
ZHEJIANG JIESHANG ARTIFICIAL INTELLIGENCE RES & DEV CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The general limitation of privacy protection algorithm makes data managers have to design new privacy protection algorithm for personalized attack mode

Method used

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  • Graph data publishing privacy protection cluster anonymity method and system
  • Graph data publishing privacy protection cluster anonymity method and system

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specific Embodiment 1

[0039] like figure 1 As shown, the embodiment of the present invention provides a clustering anonymity method for graph data publishing privacy protection, including:

[0040] Obtaining step S101, taking each user in the graph data group as a node, and obtaining the user attributes of each node and the relationship between users;

[0041] Calculation step S102, calculating the attribute similarity and structural similarity between each node and its adjacent nodes; the attribute similarity is determined by the user attributes of two adjacent nodes, and the structural similarity is determined by the two adjacent nodes The mutual relationship between users is determined;

[0042] Clustering step S103, according to the attribute similarity and structural similarity between each node and its adjacent nodes, the nodes in the group are sequentially divided into attribute clustering and structural clustering to obtain several clusters;

[0043] In the anonymizing step S104, the node...

specific Embodiment 2

[0050] like figure 2 As shown, the embodiment of the present invention provides a clustering anonymity system for graph data publishing privacy protection, including:

[0051] The obtaining module 201 is used to use each user in the graph data group as a node to obtain the user attributes of each node and the relationship between users;

[0052] The calculation module 202 is used to calculate the attribute similarity and structural similarity between each node and its adjacent nodes; the attribute similarity is determined by the user attributes of two adjacent nodes, and the structural similarity is determined by two related nodes The mutual relationship between users of adjacent nodes is determined;

[0053] The clustering module 203 is used to perform attribute clustering and structural clustering division on the nodes in the group in turn according to the attribute similarity and structural similarity between each node and its adjacent nodes, so as to obtain several clust...

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Abstract

The invention discloses a graph data publishing privacy protection cluster anonymity method and system. With each user in a graph data group as one node, the user attributes and user-to-user relationships for each node are obtained; based on the same, the attribute similarity and structure similarity between each node and its neighboring nodes are calculated, and then the nodes in the group are subjected to attribute cluster division and structure cluster division in turn according to the calculation results to obtain multiple clusters; and the nodes in each cluster are treated anonymously according to the clusters obtained from the division. The invention applies cluster analysis technology to privacy protection of graph data release; firstly, the structure similarity and attribute similarity between nodes are calculated, graph attribute cluster division and graph structure cluster division performed in turn, and finally each cluster is processed anonymously, which can protect the attribute information and structure information of users at the same time and prevent all attacks with connecting edges and attribute values as background knowledge, so as to protect the privacy and security of social network graph data publishing.

Description

technical field [0001] The invention relates to the technical fields of information technology and data mining, in particular to a clustering anonymous method and system for graph data publishing privacy protection. Background technique [0002] Currently, how to protect the privacy of graph data publishing is one of the research topics. In social network graphs, private information contained in individual nodes or edges may be leaked due to malicious theft. Generally speaking, privacy protection technology cannot define the data background knowledge that the attacker can obtain. Therefore, in dealing with complex and changeable attack models, as the background knowledge of the attacker increases, many attack variants are often generated. By combining quasi-identifier data such as the user's date of birth, gender, and zip code, attackers can often infer and target a specific individual, and then obtain other important private information of the individual. The limitation o...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30H04L12/58H04L29/06
CPCH04L63/0421H04L51/52
Inventor 尚凌辉陈鑫叶淑阳
Owner ZHEJIANG JIESHANG ARTIFICIAL INTELLIGENCE RES & DEV CO LTD
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