Incorporating security and integrity into the mining process of hybrid weighted-hashT apriori algorithm using Hadoop. (2018)

• Record Type: Journal Article
• Authors: Sumithra, R.; Paul, Sujni
• Is Part Of: International journal of data science. Volume 3:Number 3(2018)
• Page Start: 266
• Page End: 287
• Publication Date: 2018
• Subjects: data mining -- weighted apriori -- hashT -- Hadoop -- cloud -- data integrity -- data security -- eucalyptus -- apriori -- distributed mining; Big data -- Periodicals; Data mining -- Periodicals; Information storage and retrieval systems -- Periodicals; Decision making -- Data processing -- Periodicals; 005.7
• Languages: English
• ISSNs: 2053-0811

Abstract

This paper talks about the best algorithms of association rule mining (ARM), weighted and hash tree apriori algorithms in a distributed cloud platform and its enhancement as a hybrid weighted-hashT apriori algorithm and its implementation in a eucalyptus platform. Then, this research work handles the integrity and security issues of data during the process of mining. The algorithm is experimented in a cloud environment using Eucalyptus platform with VMware workstation and Hadoop distributed file system (HDFS). And also, the work evaluated how distributed implementation goes better than stand-alone implementations of weighted and hash tree apriori algorithms as well as distributed implementation. The work further studies the effectiveness of using eucalyptus Hadoop nodes and the performance changes with respect to the use of the security protocol for ensuring the security of data in the mining process.