Hybrid Framework for Privacy Preserving Data Sharing

被引:0
|
作者
Abeysekara, Ruvan Kumara [1 ]
Zhang, Weishi [1 ]
机构
[1] Dalian Maritime Univ, Dalian, Peoples R China
关键词
Privacy preserving; Data mining; Data sanitization; Data mining Algorithms;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Privacy preserving data mining has become increasingly popular and continuously evolving field of study. It allows sharing of privacy sensitive data for analysis purposes. The recent advancement in data mining technology to analyze vast amount of data has played an important role in several areas of Business processing. Data mining also opens new threats to privacy and information security if not done or used properly. Therefore this research elaborates and introduces new Hybrid Algorithm for Privacy Preserving Data Sharing. It opens the gates to touch finer points of Hybrid methodologies in privacy preserving data mining. Experiments based on the discussions of literature, mainly about data sanitization done to prove the set of hypothesis mentioned on this paper.
引用
收藏
页码:198 / 206
页数:9
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