文章基本信息

标题：PRIVATIZATION OF SENSITIVE INFORMATION IN DATA PUBLISHING USING CLOSEENESS
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作者：S.SARANYA
期刊名称：International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
印刷版ISSN：2278-1323
出版年度：2013
卷号：2
期号：9
页码：2642-2645
出版社：Shri Pannalal Research Institute of Technolgy
摘要：Privacy is an important issue in data mining while publishing the data in dataset. Many organizations distribute non-aggregate personal data for research, and they must take steps to ensure that an adversary cannot predict sensitive information pertaining to individuals with high confidence. Show that when the data contains a large number of attributes which may be considered quasi-identifiers; it becomes difficult to anonymizing the data without an unacceptably high amount of information loss. This is because an exponential number of combinations of dimensions can be used to make precise inference attacks, even when individual attributes are partially specified within a range and provide an analysis of the effect of dimensionality on k-anonymity methods. And conclude that when a data set contains a large number of attributes which are open to inference attacks, faced with a choice of either completely suppressing most of the data or losing the desired level of anonymity. To overcome these limitations, to implement a concept called "closeness". The base model of this concept is t-closeness which requires the distribution of a sensitive attribute in the overall table. In the slicing process we can perform the better data utility and membership disclosure protection
关键词：Privacy preservation; dataanonymization; ; data publishing; data security