首页 | 本学科首页   官方微博 | 高级检索  
     

动态数值敏感属性的数据隐私保护
引用本文:何贤芒,陈华辉,肖仰华,汪卫,施伯乐.动态数值敏感属性的数据隐私保护[J].计算机科学与探索,2011,5(8):740-750.
作者姓名:何贤芒  陈华辉  肖仰华  汪卫  施伯乐
作者单位:1. 宁波大学信息科学与工程学院,浙江宁波,315211
2. 复旦大学计算机科学技术学院,上海,200433
基金项目:国家自然科学基金No.61003001,61033010,60973047,90818023; 高等学校博士学科点专项科研基金No.2010007112003; 浙江省自然科学基金No.Y1091189; 王宽诚幸福基金~~
摘    要:目前动态数据的隐私保护引起了人们的广泛关注。m-invariance概念的提出,比较好地解决了动态类别敏感属性的数据隐私保护问题,但对于动态数值敏感属性却未取得任何进展。描述了动态数值敏感属性的数据隐私保护问题,提出了解决该问题的m-increment概念及其泛化算法,并通过实验数据说明了算法的实用性和效率。

关 键 词:隐私保护  k-匿名  m-不变性
修稿时间: 

Data Privacy Preservation for Dynamic Numerical Sensitive Attributes
HE Xianmang,CHEN Huahui,XIAOYanghua,WANG Wei,SHI Bole.Data Privacy Preservation for Dynamic Numerical Sensitive Attributes[J].Journal of Frontier of Computer Science and Technology,2011,5(8):740-750.
Authors:HE Xianmang  CHEN Huahui  XIAOYanghua  WANG Wei  SHI Bole
Affiliation:1. School of Information Science and Technology, Ningbo University, Ningbo, Zhejiang 315211, China 2. School of Computer Science and Technology, Fudan University, Shanghai 200433, China
Abstract:A lately privacy preservation for dynamic data has attracted great attention. The concept of m-invariance was proposed and solved the problem of data privacy preservation for dynamic categorical sensitive attributes, but it made no progress for dynamic numerical sensitive attributes. This paper analyzes the problem of data privacy pre- servation for dynamic numerical sensitive attributes, and then proposes the concept of m-increment and the corre-sponding generalization algorithm to solve the problem. Finally, the experiments demonstrate the effectiveness and efficiency of the method.
Keywords:privacy preservation  k-anonymity  m-invariance
本文献已被 CNKI 万方数据 等数据库收录!
点击此处可从《计算机科学与探索》浏览原始摘要信息
点击此处可从《计算机科学与探索》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号