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A Survey on Privacy Preserving Clustering


Affiliations
1 Dept. of CSE, Vignana Jyothi Inst. of Engg. & Tech., Hyderabad-500090, India
2 Holy Mary Inst. of Tech., Ranga Reddy Dist-501301, India
     

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Privacy Preserving Data Mining is one of the major research areas which protect the sensitive information during the mining process. In the process of data mining the data can be extracted from centralized environment or distributed environment. Privacy preserving techniques can be applied for the data in centralized environment as well as distributed environment. Privacy preserving process can also be applied on different data mining techniques like Association rule mining, clustering, classification etc. The main goal of this paper is to provide a survey on privacy preserving clustering in centralized environment which supports the individual privacy. This paper mainly presents different privacy preserving techniques used to protect the sensitive data during the clustering process of both numerical and categorical data.

Keywords

Privacy Preserving, Categorical Data, Numerical Data, Clustering.
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  • A Survey on Privacy Preserving Clustering

Abstract Views: 211  |  PDF Views: 2

Authors

V. Baby
Dept. of CSE, Vignana Jyothi Inst. of Engg. & Tech., Hyderabad-500090, India
N. Subhash Chandra
Holy Mary Inst. of Tech., Ranga Reddy Dist-501301, India

Abstract


Privacy Preserving Data Mining is one of the major research areas which protect the sensitive information during the mining process. In the process of data mining the data can be extracted from centralized environment or distributed environment. Privacy preserving techniques can be applied for the data in centralized environment as well as distributed environment. Privacy preserving process can also be applied on different data mining techniques like Association rule mining, clustering, classification etc. The main goal of this paper is to provide a survey on privacy preserving clustering in centralized environment which supports the individual privacy. This paper mainly presents different privacy preserving techniques used to protect the sensitive data during the clustering process of both numerical and categorical data.

Keywords


Privacy Preserving, Categorical Data, Numerical Data, Clustering.