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Privacy Preserving Scheme for CHUI Mining


Archana Kisan Dere , SPCOE,otur; Prof. S. A. Kahate, SPCOE,Otur


HUIs, Compact representation of HUIs, Frequent Itemset Mining, Utility mining


In data mining Frequent Itemset mining is essential. The market base analysis is the popular application in market. Large number of frequent but low revenue itemsets and lose information on valuable itemset with low selling frequencies produces by FIM model. Utility mining is essential to this problem. Discovery of high utility itemset (e.g. high profit, weight) from database is an important. Discovered HUIs may not be compact in size which degrades efficiency of mining process. Free sets, non-derivable sets and closed itemsets some compact representations available to achieve efficiency. Mining closed high utility itemsets provide as a compact and lossless representation of HUIs. The algorithm CHUD is proposed to achieve this. The third party is outsourced to mine the huge organization data. Here is need of preservation of data privacy because third party is not trustworthiness. This task have data privacy problem. We proposed a system to alleviate the load of computation, storage and processing to another party with preservation of privacy of outsourced high utility mining and also to produce the concise representation of HUIs using existing work. For privacy preservation we used one to one substitution method and Homomorphic encryption method.

Other Details

Paper ID: IJSRDV4I40566
Published in: Volume : 4, Issue : 4
Publication Date: 01/07/2016
Page(s): 536-540

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