期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2013
卷号：2
期号：3
页码：566
出版社：S&S Publications
摘要：Distributed data mining explores unknown informatio n from data sources which are distributed among several parties. Privacy of participating parties becomes great concern and sensitive information pertaining to individual parties and needs high protection when data mining occurs amo ng several parties. Different approaches for mining data securely in a distributed environment have been proposed but in the existing approaches, collusion among the participating parties might reveal responsive information about other participating parties and they suffer from the intended purposes of maintaining privacy of the individual participating sites, reducing computational co mplexity and minimizing communication overhead. The proposed method finds global frequent item sets in a distributed environment with minimal communication among parties and ensures higher degree of privacy with Data Encryption Standard (DES). The proposed method generates global frequent item sets among colluded parties without affecting mining performance and confirms optimal communicatio n among parties with high privacy and zero percentage of data leakage.
关键词：Distributed data mining; privacy; secure multiparty computation; Frequent Item sets; Data Encryption ; standard (DES).
