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Spatial point set data privacy protection matching method based on similarity binning

A technology of data privacy and similarity, applied in digital data protection, electronic digital data processing, instruments, etc., can solve problems such as data bias, traditional attacks by third parties and data owners, etc., to achieve performance adjustment and avoid collusion The effect of attack and flexible adjustment

Active Publication Date: 2020-07-28
NANJING UNIV OF POSTS & TELECOMM
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] At present, there is a very serious common problem in many emerging spatial data analysis applications: data bias
At present, the existing privacy-preserving matching technology mainly adopts the method based on the third party, and there will be the problem of traditional attack between the third party and the data owner

Method used

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  • Spatial point set data privacy protection matching method based on similarity binning
  • Spatial point set data privacy protection matching method based on similarity binning
  • Spatial point set data privacy protection matching method based on similarity binning

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Embodiment Construction

[0033] In order to deepen the understanding of the present invention, the present invention will be described in further detail below in conjunction with examples. The examples are only used to explain the present invention and do not constitute a limitation on the protection scope of the present invention.

[0034] First, give a few basic definitions:

[0035] Define 1 point set: Ps={p 1 , P 2 ,..., p n }, n≥1, expressed as a point set in a certain space, where p i =(p i ·X, p i ·Y), 1≤i≤n, represents the i-th point in the point set Ps, p i ·X, p i ·Y represents point p i The abscissa value and ordinate value of.

[0036] Define 2 point set range: For point set Ps={p 1 , P 2 ,..., p n }, n≥1, the point set range is defined as: PsE=[min(p i ·X, p i ·Y), max(p i ·X, p i ·Y)], 1≤i≤n.

[0037] Define 3 point set range union: Given two point set ranges PsE 1 =[a 1 , B 1 ],

[0038] PsE 2 =[a 2 , B 2 ], its union is defined as: PsEu = [a, b], where,

[0039] a=min(a 1 , A 2 ), b=max(b 1 , B 2...

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Abstract

The invention provides a spatial point set data privacy protection matching method based on similarity binning. The method comprises the following steps: grouping point set data range union sets at equal intervals, agreeing data grouping parameters, carrying out space division on original point set data, and obtaining grouping numbers of the point set data based on matching of the point set data and a division space; performing equal-interval binning on the similarity between the point set data and the reference value, calculating the similarity between the attribute value and the reference value, and performing binning on all similarity values by adopting an equal-interval division technology to further obtain binning combinations of all the point set data; and based on matching calculation of the point set data grouping combination number and the sub-box combination number, obtaining an identification number of the point set data according to the grouping number and the sub-box combination number of the point set data, further obtaining a matching point pair of the point set data according to the identification number, and finally exchanging the corresponding point set data according to the matched point pair. The method has the advantages of high privacy protection and precision adjustability.

Description

Technical field [0001] The present invention relates to the research field of spatial data privacy protection technology, and in particular to a method for spatial point set data privacy protection matching based on similarity binning. Background technique [0002] In recent years, with the widespread popularity of global positioning systems, sensor networks and mobile devices, a large amount of emerging spatial data has been generated. These emerging spatial data have the irreplaceable advantages of traditional spatial data, such as a large number of users and a large temporal and spatial scale. Through the analysis of emerging spatial data, it is found that laws with rich semantic metaphors can provide certain auxiliary decision-making for the construction of smart cities. [0003] At present, there is a very serious common problem for many emerging spatial data analysis applications: data bias. That is, it is difficult to achieve a complete description of the activities of use...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F21/62
CPCG06F21/6245
Inventor 张海涛冀康乐洋陈一祥李文梅
Owner NANJING UNIV OF POSTS & TELECOMM
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