Extreme Learning Machines for Internet Traffic Classification

Joseph Ghafari, Emmanuel Herbert, Stephane Senecal, Daniel Migault, Stanislas Francfort, Ting Liu

Abstract

Network packet transport services (namely the Internet) are subject to significant security issues. This paper aims to apply Machine Learning methods based on Neural Networks (Extreme Learning Machines or ELM) to analyze the Internet traffic in order to detect specific malicious activities. This is performed by classifying traffic for a key service run over the internet: the Domain Name System (DNS). The ELM models and algorithms are run on DNS traffic data extracted from operating network for botnet detection.