A Botnet Taxonomy and Detection Approaches
Abstract
This paper focuses on the study of Botnet and its Command and Control (C&C) structure. It also reviews the state of the art in machine learning-based Botnet detection system. In order to survive, Botnet implemented various evasion techniques, and one of the famousevasion technique is by manipulating an encrypted channel to perform their C&C communication. Therefore, we also look into the capabilities of machine learning approaches to detect these particular Botnet activities via encrypted channels. From the study, we show the effectiveness of machine learning in Botnet detection over an encrypted channel. The paper concludes by highlighting the limitations of the existing Botnet detection approaches and the way forward.