ANN based Multi-Class classification of P2P Botnet

Abstract

In the virtual world, most of the cyber-attacks done by Botnet. The Botnet is one of the most versatile threats because of its controlling from a remote place. Most of the existing Botnet detection approaches focused on binary classification based on traditional machine learning, and these have some limitations. In this paper, multiclass classification method has been proposed for Botnet detection based on Artificial Neural Networks with some variations. The proposed model is used to detect different types of Botnet from a large pool of Botnet families. This paper has used a dataset consisting of seven different classes to train and test the model. In this work, we got promising results in terms of accuracy, 99.04%, and other performance measures. The accuracy of the proposed is better when compared with other traditional machine learning models when evaluated using the same dataset.