Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Optimized SNS (social network service) graph data publication privacy protection method

A social network and privacy protection technology, applied in the field of privacy protection for optimized social network graph data publishing, can solve problems such as personal privacy leakage

Active Publication Date: 2013-09-04
GUANGXI NORMAL UNIV
View PDF5 Cites 29 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, if these data are released directly, a large amount of personal privacy will be leaked.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Optimized SNS (social network service) graph data publication privacy protection method
  • Optimized SNS (social network service) graph data publication privacy protection method
  • Optimized SNS (social network service) graph data publication privacy protection method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0027] An optimized social network graph data publishing privacy protection method is characterized in that it comprises the following steps:

[0028] (1) Social network data, due to the complexity of its relationship, is generally represented by graph data nodes. This algorithm protects the degree attribute of social network graph data. First, an undirected graph G(V, E) is used to abstract the social network, where V is a finite set of vertices, representing individuals or groups in the social network, and E is a binary relationship on V, representing the relationship in the social network, such as friends , classmates, relatives and other relationships.

[0029] (2) Calculate the degree d of each vertex in the undirected graph G(V, E) i , where degree d i Indicates the number of binary relations associated with the i-th vertex, where i=1, 2, ..., n. For a graph G with n vertices, each vertex has a degree, the sequence of degrees d G is an n-dimensional vector.

[0030]...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses an optimized SNS graph data publication privacy protection method. The method includes firstly abstracting SNS data into an undirected graph and generating a degree sequence for the undirected graph; secondly, dividing the degree sequence into groups to build an anonymous degree sequence; and lastly, performing the processes of edge adding and vertex adding on the anonymous degree sequence. Therefore, every individual or group in the SNS data can have at least k other individuals or groups with the same attribute, and an attacker can only position the at least k individuals or groups according to background information, further the individual or group privacy information of participants of the SNS can be protected effectively. With a high efficiency, the optimized SNS graph data publication privacy protection method can be applied to the privacy protection treatment of large-scale SNS data. Besides, the optimized SNS graph data publication privacy protection method has little information loss during the data reconstruction treatment.

Description

technical field [0001] The invention relates to the field of social network information release security, in particular to an optimized privacy protection method for social network graph data release. Background technique [0002] In recent years, with the rapid development of the Internet, social network products, such as Facebook, Twitter, WeChat, Weibo, Kaixin, etc., have become more and more closely related to personal life. Information about individuals is more abundant and complete on the Internet, and the virtual world and the real world are gradually intersecting. When users use social networking services, they will generate a large amount of personal privacy data, which will be provided to third parties for government regulation, business purposes or research needs. However, if these data are released directly, a large amount of personal privacy will be leaked. Therefore, these data need to be processed for privacy protection before release. [0003] Glossary ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06F21/60
Inventor 李先贤刘鹏焦佳
Owner GUANGXI NORMAL UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products