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  • 标题:An Advanced Data Transformation Algorithm for Categorical Data Protection
  • 本地全文:下载
  • 作者:Dnyaneshwar Pandurang Naik ; Anjana N. Ghule
  • 期刊名称:International Journal of Computer Science and Information Technologies
  • 电子版ISSN:0975-9646
  • 出版年度:2013
  • 卷号:4
  • 期号:6
  • 页码:899-902
  • 出版社:TechScience Publications
  • 摘要:The objective of data mining is extracted new, important and required information and knowledge from the large databases. Privacy preserving in the data mining process is one of the latest research areas which deals with the side effects of the data mining techniques such as viewing of personal or private or sensitive or confidential data to the public. The results of data mining techniques may produce complete data; but this resulting data contain private or sensitive information. This sensitive information should be modified before giving it to the public. For protecting the confidential or sensitive information, it is necessary to modify of the sensitive data items in a data set such that it should not affect the importance of the original objective of data mining. There are various types of masking techniques are available and can be used for protecting sensitive data items. In this research work, the proposed system makes use of perturbative system with applying encryption technique to sensitive data items.
  • 关键词:Data Transformation; Categorical Data;Clustering; Sensitive Attribute; Privacy Preserving
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