A Multi Sensitive Attribute Data Inverse Clustering Privacy Preserving Algorithm for Sensitivity Attack

ZHANG Bing; YANG Jing; ZHANG Jian-pei; XIE Jing

doi:10.3969/j.issn.0372-2112.2014.05.010

您当前的位置：

首页 >

文章列表页 >

A Multi Sensitive Attribute Data Inverse Clustering Privacy Preserving Algorithm for Sensitivity Attack

更新时间：2025-07-16

- A Multi Sensitive Attribute Data Inverse Clustering Privacy Preserving Algorithm for Sensitivity Attack
- Acta Electronica Sinica Vol. 42, Issue 5, Pages: 896-903(2014)
- 作者机构：
  
  哈尔滨工程大学计算机科学与技术学院,黑龙江,哈尔滨,150001
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.0372-2112.2014.05.010
  CLC： TP309.2
- Published：2014
- 稿件说明：
移动端阅览
ZHANG Bing, YANG Jing, ZHANG Jian-pei, et al. A Multi Sensitive Attribute Data Inverse Clustering Privacy Preserving Algorithm for Sensitivity Attack[J]. Acta Electronica Sinica, 2014, 42(5): 896-903.
DOI：

ZHANG Bing, YANG Jing, ZHANG Jian-pei, et al. A Multi Sensitive Attribute Data Inverse Clustering Privacy Preserving Algorithm for Sensitivity Attack[J]. Acta Electronica Sinica, 2014, 42(5): 896-903. DOI： 10.3969/j.issn.0372-2112.2014.05.010.

摘要

针对传统

-多样性模型仅考虑等价类中敏感值形式上的差异，而忽略敏感值的敏感度差异，且难以抵御一种新的攻击方式——敏感性攻击的问题，提出了一种使用逆文档频率IDF度量敏感值的敏感度的方法，并使用属性分解的方式构造敏感组，以避免多敏感属性数据表的

属性泛化造成的高信息损失.同时，还提出了一种面向敏感性攻击的多敏感属性(

…

em>d)-多样性隐私保护算法MICD，该算法通过敏感度的逆聚类实现敏感组中敏感值的敏感度差异，以提高多敏感属性数据表抵御敏感性攻击的能力.实验结果表明，MICD算法能够较好的抵御敏感性攻击，且具有较小的信息损失量.

Abstract

In allusion to

-diversity model not considering sensitivity differences between the sensitive attributes

a new attack pattern which named sensitivity attack was proposed.Secondly

a new sensitive groups constructing method which based on sensitive attributes decomposition was proposed

and a keyword weight evaluation method called IDF was used to measure the sensitivity of the sensitive values.At the same time

a multi sensitive attributes (

…

)-diversity privacy preserving method for sensitivity attack which called MICD was proposed

which guar

anteed the sensitivity difference between sensitive values in sensitive groups by sensitivity inverse clustering.Experiment results demonstrated that the MICD algorithm could better protect sensitive attributes against sensitivity attack

and more effective on information loss.

关键词

Keywords

references

Views

1454

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

A Method for Private Video Action Recognition Based on Visual Audio Complementary and Semantic Clarity

Relations Between Several Classical Privacy Notions

Achieving (α,k)-Anonymity via Clustering in Data Publishing

Privacy Preserving Based on Vector Similarity for Weighted Social Networks

Related Author

TANG Jin-hui

YAN Rui

PAN Li-yong

FU Xiao-de

LI Ze-chao

LI Zhe-tao

HUANG Cheng

WANG Ping

Related Institution

School of Computer Science and Engineering， Nanjing University of Science and Technology

College of Information Science and Technology, Jinan University

School of Mathematics and Computational Science, Xiangtan University

School of Computer Science and Artificial Intelligence, Lanzhou University of Technology

School of Coputer Science, Fudan University

⁰