Behaviour analysis of machine learning algorithms for detecting P2P botnets

Abstract

Botnets have emerged as a powerful threat on the Internet as it is being used to carry out cybercrimes. In this paper, we have analysed some machine learning techniques to detect peer to peer (P2P) botnets. As the detection of P2P botnets is widely unexplored area, we have focused on it. We experimented with different machine learning (ML) algorithms to compare their ability to classify the botnet traffic from the normal traffic by selecting distinguishing features of the network traffic. Experiments are performed on the dataset containing the traces of various P2P botnets. Results and tradeoffs obtained of different ML algorithms on different metrics are presented at the end of the paper.