[1]胡新平,孙志挥,张柏礼,等.基于敏感元组的隐私数据保护方法[J].东南大学学报(自然科学版),2010,40(5):911-916.[doi:10.3969/j.issn.1001-0505.2010.05.006]
 Hu Xinping,Sun Zhihui,Zhang Baili,et al.Privacy data preserving method based on sensitive tuples[J].Journal of Southeast University (Natural Science Edition),2010,40(5):911-916.[doi:10.3969/j.issn.1001-0505.2010.05.006]
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基于敏感元组的隐私数据保护方法()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
40
期数:
2010年第5期
页码:
911-916
栏目:
计算机科学与工程
出版日期:
2010-09-20

文章信息/Info

Title:
Privacy data preserving method based on sensitive tuples
作者:
胡新平12 孙志挥1 张柏礼1 董建成2
1 东南大学计算机科学与工程学院,南京 210096; 2 南通大学数字医学研究所,南通 226001
Author(s):
Hu Xinping12 Sun Zhihui1 Zhang Baili1 Dong Jiancheng2
1 School of Computer Science and Engineering, Southeast University, Nanjing 210096, China
2 Institute of Digital Medicine, Nantong University, Nantong 226001, China
关键词:
k-匿名 隐私保护 敏感元组 敏感元组密度 敏感元组权重
Keywords:
k-anonymity privacy-preserving sensitive tuples sensitive tuple density weight of sensitive tuple
分类号:
TP311
DOI:
10.3969/j.issn.1001-0505.2010.05.006
摘要:
针对现有k-匿名隐私保护方法的缺点, 提出了3种基于敏感元组的隐私数据发布方法.首先,通过定义敏感元组,设计了只保护隐私信息的朴素敏感元组匿名方法(NSTAM). 然后,在引入敏感元组密度的基础上,提出了一种扩展的敏感元组保护方法(e-STAM); 该方法通过对敏感元组进行mk-匿名运算,引入(1-m)k个非敏感元组,并同等概化引入的非敏感元组,使得匿名后每个分组中的敏感元组密度满足用户设定的阈值m.最后,针对实际应用中发布数据的敏感度差异,引入了加权敏感元组密度概念,并设计了加权的敏感元组数据保护方法(WSTAM); 该方法通过对敏感值和敏感元组赋予不同的权重,实现对敏感元组的区别保护.理论分析和实验结果表明, 这3种算法能够提高发布数据的精度,保证敏感数据的安全度,因此是有效可行的.
Abstract:
To solve the problem of the current k-anonymity privacy-preserving method, three kinds of privacy-preserving methods based on sensitive tuples are proposed. First, through defining sensitive tuples, a naive sensitive tuple anonymity method(NSTAM)which only protects sensitive information is presented. Then, the sensitive tuple density is introduced, and an extended sensitive tuple anonymity method(e-STAM)is presented. In this method, after executing mk-anonymity operations for the sensitive tuples,(1-m)k non-sensitive tuples are added and generalized at the same degree in order to ensure that the density of the sensitive tuples in each group is satisfied with the defined threshold m. Finally, according to the sensitivity difference among the published data, the weight sensitive tuple density is introduced, and a weighted STAM(WSTAM)is further proposed. The distinct protections for different sensitive tuples are realized by assigning different weights to sensitive tuples. The theoretical analysis and experimental results indicate that the three methods designed are feasible and effective because they can improve the accuracy of the published data and the security of the sensitive data.

参考文献/References:

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[8] 杨晓春,刘向宇,王斌,等.支持多约束的k-匿名化方法[J].软件学报,2006,17(5):1222-1231.
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备注/Memo

备注/Memo:
作者简介: 胡新平(1970—),男,博士生,副教授; 孙志挥(联系人),男,教授,博士生导师,szh@seu.edu.cn.
基金项目: 教育部高等学校博士学科点专项科研基金资助项目(20040286009)、南通市重大科技创新专项资助项目(XA2009001)、南通市科技应用计划资助项目(K2009010).
引文格式: 胡新平,孙志挥,张柏礼,等.基于敏感元组的隐私数据保护方法[J].东南大学学报:自然科学版,2010,40(5):911-916. [doi:10.3969/j.issn.1001-0505.2010.05.006]
更新日期/Last Update: 2010-09-20