Privacy-preserving data publishing methods for multiple numerical sensitive attributes

被引：1
|
作者：
Liu T. [1 ]
Ni W. [1 ]
Chong Z. [1 ]
Zhang Y. [1 ]
机构：
[1] School of Computer Science and Engineering, Southeast University
来源：
Dongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Southeast University (Natural Science Edition) | 2010年 / 40卷 / 04期
关键词：
Data publishing; Multiple sensitive attributes; Numerical data; Privacy preserving;
D O I：
10.3969/j.issn.1001-0505.2010.04.007
中图分类号：
学科分类号：
摘要：
Proximity breach is a privacy threat specific to numerical sensitive attributes in data publication. This paper tries to remedy the problem by introducing a novel principle called l-MNSA(l-multi numerical sensitive attribute) approach based on the idea of lossy join. Firstly, a data publishing algorithm concentrating on tables with only one numerical sensitive attribute, i.e. l-SNSA(l-single numerical sensitive attribute) algorithm, is proposed, in which the sensitive attribute is grouped by their values. Then, the idea of shortest distance is suggested. By unifying the sensitive attributes value and grouping them by their shortest distance, l-MNSA algorithm is proposed. Compared with previous algorithm for single sensitive attribute, l-MNSA can provide better protection to the multi numerical sensitive attributes. The results show that the minimum difference of data published by l-MNSA is reduced by 10% compasing to that of l-SNSA, meanwhile, the time complexity is O(nlgn). The l-MNSA can better balance the published data's security and availability, being feasible and effective.
引用
收藏
页码：699 / 703
页数：4
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