Taxonomy on RapidMiner Using Machine Learning

6 Pages Posted: 14 Jun 2019

See all articles by Ginika Mahajan

Ginika Mahajan

Manipal University Jaipur

Bhavna Saini

Manipal University Jaipur

Tai Almas

Manipal University Jaipur

Date Written: February 23, 2019

Abstract

Malware Classification is an important factor in security of Computer and Network Systems. Malware Classification means to classify the malware samples into their respective families and subfamilies. In this work we have used malware dataset having multiple signatures. Our objective here is to provide efficient machine learning algorithm which provide best accuracy for classification of malware into their respective families. We use RapidMiner tool and four different machine learning algorithms to analyze dataset. Best accuracy we get is of 64.05% using Decision Tree algorithm and split validation technique for splitting of dataset into training and test set.

Suggested Citation

Mahajan, Ginika and Saini, Bhavna and Almas, Tai, Taxonomy on RapidMiner Using Machine Learning (February 23, 2019). Proceedings of International Conference on Sustainable Computing in Science, Technology and Management (SUSCOM), Amity University Rajasthan, Jaipur - India, February 26-28, 2019. Available at SSRN: https://ssrn.com/abstract=3363071 or http://dx.doi.org/10.2139/ssrn.3363071

Ginika Mahajan (Contact Author)

Manipal University Jaipur ( email )

VPO - Dehmi Kalan, Tehsil Sanganer
Off Jaipur - Ajmer Expressway
Jaipur, 303007
India

Bhavna Saini

Manipal University Jaipur ( email )

Dehmi Kalan,
Near GVK Toll Plaza, Jaipur-Ajmer Exp
Jaipur, RI Rajasthan 303007
India

Tai Almas

Manipal University Jaipur

Dehmi Kalan,
Near GVK Toll Plaza, Jaipur-Ajmer Exp
Jaipur, RI Rajasthan 303007
India

Register to save articles to
your library

Register

Paper statistics

Downloads
20
Abstract Views
111
PlumX Metrics