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A multi-attribute data deprivation method considering practicability

A multi-attribute, practical technology, applied in the field of information hiding, can solve the problem of not having enough practical feedback from users

Active Publication Date: 2019-09-20
ZHEJIANG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] However, the above-mentioned existing privacy protection methods do not provide sufficient practical feedback to users.

Method used

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  • A multi-attribute data deprivation method considering practicability
  • A multi-attribute data deprivation method considering practicability
  • A multi-attribute data deprivation method considering practicability

Examples

Experimental program
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Embodiment Construction

[0044] In this embodiment, the data set used is part of the public microdata sample data (PUMS) collected during the 2015 Wyoming State Census. This data set contains a lot of information about households.

[0045] The method for depriving privacy of multi-attribute data considering practicality in this embodiment includes the following steps:

[0046] Step 1: Import the preprocessed multi-attribute data and extract the following four attributes from the data set: "Insurance Expenses" (annual), "Family Income" (in the past year), "Children" (in the family under 18) The number of persons), and the "elderly" (the number of persons over 65 in the family); where family income is considered a sensitive attribute that needs to be protected.

[0047] Step 2: Define the necessary attributes and sensitive attributes according to the attribute description, set the pre-grouping rules of the necessary attributes, define the order of the necessary attributes according to the attribute characteri...

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PUM

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Abstract

The invention discloses a multi-attribute data privacy removing method taking practicability into consideration. The method comprises the following steps of S1, importing preprocessed multi-attribute data; S2, defining necessary attributes and sensitive attributes according to attribute descriptions, setting pre-grouping rules of the necessary attributes, and defining the sequences of the necessary attributes according to the attribute characteristics; S3, establishing a privacy exposure risk tree, and taking the attribute sequences and the pre-grouping rules in the step S2 as hierarchical sequences of the privacy exposure risk tree and the basis for generating branches of each hierarchy; and S4, measuring result information according to coding risks of the sensitive attributes on nodes and borders of the privacy exposure risk tree. According to the method, the suitable method can be flexibly selected from a plurality of common grammar anonymization and difference privacy models for solving the privacy problem, thereby satisfying various privacy demands for different data. Through utilization of special advantages of the privacy exposure risk tree, a multi-dimensionally aggregated space is designed compactly.

Description

Technical field [0001] The invention relates to the technical field of information hiding, in particular to a method for depriving privacy of multi-attribute data considering practicability. Background technique [0002] Before displaying the data or making the data public for analysis, the data owner needs to consider whether the data involves sensitive information of the individual. If related issues are involved, the data needs to be deprived of privacy in advance. [0003] The prior art Zhongguan methods mainly include the following three aspects: First, privacy protection models. In the field of privacy protection, many automatic methods have been proposed. Among them, semantic anonymity models and differential privacy models are the two most common types of privacy protection models. Among them k-anonymity (L. Sweeney. k-anonymity: A model for protecting privacy. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 10(05): 557-570, 2002.), l-diversity...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F21/62
Inventor 陈为王叙萌关会华陈文龙劳天溢
Owner ZHEJIANG UNIV
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