An approach for prevention of privacy breach and information leakage in sensitive data mining

被引:26
作者
Prakash, M. [1 ]
Singaravel, G. [2 ]
机构
[1] Anna Univ, KSR Coll Engn, Dept Comp Sci & Engn, Tiruchengode, Tamilnadu, India
[2] Anna Univ, KSR Coll Engn, Dept Informat Technol, Tiruchengode, Tamilnadu, India
关键词
Anonymization; Data mining; Privacy; Privacy preserving; Privacy preserving techniques; Sensitive data publishing;
D O I
10.1016/j.compeleceng.2015.01.016
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Government agencies and many non-governmental organizations often need to publish sensitive data that contain information about individuals. The sensitive data or private data is an important source of information for the agencies like government and non-governmental organization for research and allocation of public funds, medical research and trend analysis. The important problem here is publishing data without revealing the sensitive information of individuals. This sensitive or private information of any individual is essential to several data repositories like medical data, census data, voter registration data, social network data and customer data. In this paper a personalized anonymization approach is proposed which preserves the privacy while the sensitive data is published. The main contributions of this paper are three folds: (i) the definition of the data collection and publication process, (ii) the privacy framework model and (iii) personalized anonymization approach. The experimental analysis is presented at the end; it shows this approach performs better over the distinct l-diversity measure, probabilistic l-diversity measure and k-anonymity with t-closeness measure. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:134 / 140
页数:7
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