Over the past ten to fifteen years botnets have gained the attention of researchers worldwide. A great deal of effort has been given to developing systems that would efficiently and effectively detect the presence of a botnet. This unique problem saw researchers applying machine learning (ML) to solve this problem. In this paper we provide a brief overview the different machine learning (ML) methods and the part they play in botnet detection. The main aim of this paper is to clearly define the role different ML methods play in Botnet detection. A clear understanding of these roles are critical for developing effective and efficient real-time online detection approaches and more robust models.
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