Classification of Malevolent and Benevolent Network Traffic

  • Aayushi Jain, Vimal Kumar

Abstract

Technological advancement has inclined people towards digital world. According to Global Digital Report, around 4.39 billion people are using internet and sharing their vital information over it. Due to such high usage, digital world has become the hub of information thereby, leading to increase in number of intruders. All vital information traverses through network and it is very important to protect our significant data by classifying our network traffic.We need to apply various techniquesto differentiate between malicious or non-malicious data packets. Due to continuous evolution of technology and dynamic nature of internet, traditional models for network traffic classification like port number and payload classification are not competent enough.The main challenge for the researchers is to classify encrypted and encapsulated traffic.This gap has provided us scope to try and use machine learning for classification of network traffic effectively. Machine learning approach helps us in extracting knowledge from the encrypted traffic.

Keywords: Machine Learning Approach, Network Traffic Classification

Published
2020-05-29
Section
Articles