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

R. Sumithra and Sujni Paul

International Journal of Data Science, 2018, vol. 3, issue 3, 266-287

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.

Keywords: data mining; weighted apriori; hashT; Hadoop; cloud; data integrity; data security; eucalyptus; apriori; distributed mining. (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=94506 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijdsci:v:3:y:2018:i:3:p:266-287

Access Statistics for this article

More articles in International Journal of Data Science from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().