Method for processing big data based on l-diversity rules and MDAV algorithm

A big data and algorithm technology, applied in the field of privacy security, can solve the problems of long computing time, comrade attack, large amount of information loss, etc., to achieve the effect of small amount of information loss, resisting homogeneous attack, and maximizing privacy protection

Active Publication Date: 2017-10-20
XIDIAN UNIV
View PDF3 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] The existing l-diversity rule effectively avoids the problem that k-anonymity cannot resist gay attacks, but it still has the problems of high time complexity of k-anonymity algorithm, long calculation time, and large amount of information loss
[0009] The MDAV algorithm is a classic fi

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
  • Method for processing big data based on l-diversity rules and MDAV algorithm
  • Method for processing big data based on l-diversity rules and MDAV algorithm
  • Method for processing big data based on l-diversity rules and MDAV algorithm

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0035] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, but not to limit the present invention.

[0036] The present invention improves the MDAV algorithm to satisfy the l-diversity rule and generates a new algorithm "(l,d,e)-MDAV algorithm". Compared with the MDAV algorithm, it guarantees high algorithm efficiency and low information loss. Low risk of information leakage and ability to resist gay attacks.

[0037] A detailed description will be given below in conjunction with the drawings.

[0038] 1.1 Related calculation formula

[0039] According to the nature of attributes, data can be divided into continuous data and sub-type data: (1) Continuous data, also known as numerical data, can directly perform mathematical...

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 belongs to the technical field of privacy protection of a database and discloses a method for processing big data based on l-diversity rules and an MDAV algorithm. According to the method, the MDAV algorithm is improved, a new algorithm, namely an ''(l,d,e)-MDAV algorithm'' is generated, and compared with MDAV, the new algorithm can resist homogeneity attacks and effectively reduce information leakage risks while guaranteeing high efficiency and low information loss. It is proved through experiments that the new algorithm has a good effect on processing anonymization of data tables. According to the method, a manually-given difference value with a center of mass has personalized further research value. A user can set an e value according to the demand for self-confidentiality, and maximum privacy protection and a minimum leakage risk can be realized.

Description

technical field [0001] The invention belongs to the technical field of privacy security in data release, and proposes a method for processing big data based on the l-diversity rule and the MDAV algorithm based on the l-diversity rule and the MDAV algorithm. Background technique [0002] The issue of privacy protection in data publishing was first raised in the field of statistical leakage control, and then gradually penetrated into the entire information technology field. In the field of statistical leak control, methods such as micro-aggregation, randomization, sampling, and adding white noise are mainly used to protect information. While trying to ensure the statistics and availability of processed data and the security of private information, more information is retained. Useful information, balance the relationship between data confidentiality and availability. After years of development, the privacy protection technology released in the data mainly focuses on two aspec...

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): G06F21/62
CPCG06F21/6254
Inventor 李晖吴良俊
Owner XIDIAN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products