A Randomized Privacy Preserving Method for Graph Data Publishing

A technology for randomizing privacy and graph data, applied in the fields of digital data protection, electronic digital data processing, computer security devices, etc., can solve the problems of data release privacy leakage, etc., and achieve the effect of good probability distribution characteristics

Active Publication Date: 2019-05-10
GUANGXI NORMAL UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The technical problem to be solved by the present invention is the problem of privacy leakage in existing data publishing, and a randomized privacy protection method for graph data publishing is provided

Method used

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  • A Randomized Privacy Preserving Method for Graph Data Publishing
  • A Randomized Privacy Preserving Method for Graph Data Publishing
  • A Randomized Privacy Preserving Method for Graph Data Publishing

Examples

Experimental program
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Embodiment Construction

[0027] This embodiment takes figure 1 The original graph network data shown is taken as an example to illustrate the proposed randomized graph data publishing privacy protection method.

[0028] figure 1 The original graph data shown is simple undirected graph data G=(V, E), where V is an entity participating in the network, and E is a relationship between entities.

[0029] Adjacency matrices are commonly used in computers to store and process graph data. Adjacency matrix A=[a ij ] is an n×n 0-1 matrix, where when node v i and v j a ij = 1, otherwise a ij =0. figure 1 The original graph data shown, that is, the matrix of the adjacency matrix A corresponding to the graph data G is expressed as:

[0030]

[0031] The adjacency matrix A is a symmetric matrix, and each edge in the data corresponds to two symmetric non-zero entries in the matrix. In order to realize the random disturbance algorithm of the present invention, the upper triangular matrix B is introduced. ...

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PUM

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Abstract

The invention discloses a randomized privacy protection method for graph data release. Graph data are processed through a randomized disturbance method, and the data processed by the randomized privacy protection method can be shared and released to an unspecified third party without infringing privacy information of a user included in the data. Meanwhile, the processed graph data have a high probability distribution feature, and relevant parameters can be adjusted flexibly according to the requirement on privacy protection intensity.

Description

technical field [0001] The invention relates to the technical field of data release, in particular to a randomized privacy protection method for graph data release. Background technique [0002] Graph data can be used to describe the predation relationship between species, the semantic connection between words, the network connection between computers, the citation relationship between scientific research articles, the traffic flow relationship, and even the human emotional relationship. When the entity nodes in the graph data involve people, if the data is directly released or improperly shared with a third party, privacy leakage issues may arise. For example, if the attacker knows that the attacked object has two friends, and there is only one node with two friends in the published data, the target node can be relocated in the published data. Therefore, it is necessary to process the data before the data is released to protect the privacy of users in the data from being l...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F21/62
CPCG06F21/6254
Inventor 刘鹏李先贤王利娥
Owner GUANGXI NORMAL UNIV
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