Machine Learning based Traffic Classification using Statistical Analysis

Abstract

In this paper, Automated system is built which contains processing of captured packets from the network. Machine learning algorithms are used to build a traffic classifier which will classify the packets as malicious or non-malicious. Previously, many traditional ways were used to classify the network packets using tools, but this approach contains machine learning approach, which is an open field to explore and has provided outstanding results till now. The main aim is to perform traffic monitoring, analyze it and govern the intruders. The CTU-13 is a dataset of botnet traffic which is used to develop traffic classification system based on the features of the captured packets on the network. This type of classification will assist the IT administrators to determine the unknown attacks which are broadening in the IT industry.