TITLE:
Malware Images Classification Using Convolutional Neural Network
AUTHORS:
Espoir K. Kabanga, Chang Hoon Kim
KEYWORDS:
Malware, Convolutional Neural Network, Malware Classification
JOURNAL NAME:
Journal of Computer and Communications,
Vol.6 No.1,
December
29,
2017
ABSTRACT: Deep learning has been recently achieving a great performance for malware classification task. Several research studies such as that of converting malware into gray-scale images have helped to improve the task of classification in the sense that it is easier to use an image as input to a model that uses Deep Learning’s Convolutional Neural Network. In this paper, we propose a Con-volutional Neural Network model for malware image classification that is able to reach 98% accuracy.