文章基本信息

标题：Privacy Preservation Of Sensitive Attributes Using Hybrid Approach
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作者：M. Geetha ; V. Uma Rani
期刊名称：International Journal of Engineering and Computer Science
印刷版ISSN：2319-7242
出版年度：2014
卷号：3
期号：4
页码：5507-5513
出版社：IJECS
摘要：Privacy Preserving Record Linkage (PPRL) is widely used in data mining applications which aims tointegrate data from different heterogeneous data sources while hiding the private information. In thispaperwe propose a new algorithm for merging two datasets using Sorted Neighborhood Deterministicapproach and a new Preservation algorithm that uses Pattern mining over dynamic queries. In contrast to theexisting techniques our approach guarantees strong privacy less computational complexity and is scalableover large datasets. We provide empirical evidences to prove that our method is secure, fast and efficientthan the existing methods.
关键词：PPRL; Sorted Neighborhood Deterministic approach; Pattern Mining