High-dimensional private data publishing method based on Bayesian network attribute clustering analysis technology

A Bayesian network and privacy data technology, applied in the field of high-dimensional privacy data release, can solve the problems of high-dimensional privacy data plus noise publishing error, low efficiency, poor usability, etc., to preserve correlation, shorten running time, The effect of ensuring data privacy security and availability

Pending Publication Date: 2020-12-25
HEFEI CITY COULD DATA CENT +1
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AI Technical Summary

Problems solved by technology

[0009] The purpose of the present invention is to solve the defects of high-dimensional privacy data plus noise publishing error, poor usability, and low efficiency, and provide a high-dimensional privacy data publishing method based on Bayesian network attribute clustering analysis technology to solve the above problems

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  • High-dimensional private data publishing method based on Bayesian network attribute clustering analysis technology
  • High-dimensional private data publishing method based on Bayesian network attribute clustering analysis technology
  • High-dimensional private data publishing method based on Bayesian network attribute clustering analysis technology

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Embodiment Construction

[0061] In order to have a further understanding and understanding of the structural features of the present invention and the achieved effects, the preferred embodiments and accompanying drawings are used for a detailed description, as follows:

[0062] Such as figure 1 and figure 2 As shown, a high-dimensional privacy data publishing method based on Bayesian network attribute clustering analysis technology described in the present invention includes the following steps:

[0063] The first step is the acquisition of high-dimensional data: obtain the high-dimensional data to be released, perform attribute induction on the high-dimensional data, and form a high-dimensional data attribute set.

[0064] The second step is the clustering of attribute subsets: by calculating the correlation between high-dimensional data attributes, the attribute clustering method is used to divide the high-dimensional attribute set into c attribute subsets, and then the original data is divided in...

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Abstract

The invention relates to a high-dimensional private data publishing method based on a Bayesian network attribute clustering analysis technology. Compared with the prior art, the defects that high-dimensional private data noise adding publishing is large in error, poor in availability and low in efficiency are overcome. The method comprises the following steps: acquiring high-dimensional data; clustering and dividing the attribute subsets; constructing a noise-added Bayesian network; generating noise adding condition distribution; publishing of synthetic datasets. In a high-dimensional big dataenvironment, the operation time of a data release algorithm can be shortened while the data privacy security and availability are ensured, and effective release of private data in the high-dimensional big data environment is realized.

Description

technical field [0001] The invention relates to the technical field of high-dimensional data privacy processing, in particular to a high-dimensional privacy data publishing method based on Bayesian network attribute clustering analysis technology. Background technique [0002] With the continuous development and application of information technology, rich data resources have been accumulated in the information systems of all walks of life, and these data often contain huge research value. However, since the original data usually contains many personal private information, publishing it directly will lead to the leakage of sensitive information. Therefore, before the data is released, it needs to be processed with special privacy protection technology. Traditional privacy protection techniques (such as k-anonymity, l-diversity and t-secrecy, etc.) can protect personal privacy to a certain extent, but they are difficult to resist background knowledge attacks, and are far from...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F21/62G06K9/62
CPCG06F21/6245G06F18/23G06F18/29
Inventor 陈恒恒刘胜军谢飞倪志伟陈千李海松卜繁耀朱旭辉
Owner HEFEI CITY COULD DATA CENT
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