文章基本信息

标题：Efficient Protocol for Privacy Preserving Association Rule Mining
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作者：P. R. Deshmukh ; Prajakta Jaswante
期刊名称：International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
印刷版ISSN：2278-1323
出版年度：2015
卷号：4
期号：11
页码：4202-4207
出版社：Shri Pannalal Research Institute of Technolgy
摘要：Data mining is the most fast growing area today which is used to extract important knowledge from large data collections but often these collections are divided among several parties. This paper addresses secure mining of association rules over horizontally partitioned data. This method incorporates a protocol is that of Kantarcioglu and Clifton well known as K&C protocol. This protocol is based on an unsecured distributed version of the Apriori algorithm named as Fast Distributed Mining (FDM) algorithm of Cheung et al. The main ingredients in our protocol are two novel secure multi-party algorithms one that computes the union of private subsets that each of the interacting players hold and another that tests an element is secured or not.This protocol offers enhanced privacy with respect to the earlier protocols.
关键词：Privacy Preserving Data Mining; Distributed Computation; Frequent Itemsets; Association Rules