Privacy Preserving Distributed Data Mining |
Author(s): |
| Tank Mayurkumar B. , L.D. COLLEGE OF ENGINEERING; Tushar A. Champaneria |
Keywords: |
| Privacy preserving distributed data mining, PPDDM, Secure Data Mining, PPDM, multi-party data mining, Frequent Item set Mining |
Abstract |
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The aim of Privacy Preserving Distributed Data Mining is to extract relevant knowledge from large amount of data while protecting at the same time sensitive information .Due to personal interests , medical databases or business interest privacy is needed .Due to privacy infringement while performing the data mining operation this not often possible to utilize large databases for scientific or financial research. For better decision making we need to perform multi-party computation by combining the database of two or more than two parties ,which can not guarantee security .To address this problem ,several privacy preserving distributed data mining techniques are used .In this paper Apriory based distributed, privacy preserving Frequent Item set Mining algorithms are designed to fit in the Secure Multiparty Computation model for privacy preserving computation. |
Other Details |
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Paper ID: IJSRDV3I40865 Published in: Volume : 3, Issue : 4 Publication Date: 01/07/2015 Page(s): 1579-1582 |
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