文章基本信息

标题：Privacy Preserving Association Rule Mining without Trusted Party for Horizontally Partitioned Databases
本地全文：下载
作者：N V Muthu Lakshmi ; K Sandhya Rani
期刊名称：International Journal of Data Mining & Knowledge Management Process
印刷版ISSN：2231-007X
电子版ISSN：2230-9608
出版年度：2012
卷号：2
期号：2
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Many data mining techniques are available to explore useful hidden information from large databases. Among these, association rule mining has wide applications to discover interesting relationships among attributes. The issue of privacy arises when the data is distributed among multiple sites and no site owner wishes to provide their private data to other sites but they are interested to know the global results obtained from mining process. In this paper a new model is proposed which utilizes hash based secure sum cryptography technique when no site can be treated as trusted party to find global association rules for horizontally partitioned databases.
关键词：Privacy Preserving Association Rule; Horizontally Partitioned Database; Cryptography Technique; Hash;Based Secure Sum