Enhancing Performance of Network Traffic Classification using Machine Learning: A Review

Abstract

The current study focuses on improving performance in the situation of network categorization. In order to accomplish the goal, the study utilized a machine learning method. The network traffic classification technique is a data categorization approach based on network type traffic. The network traffic classification process necessitates data collection, pre-processing, feature extraction, classification, and performance analysis. The two main objectives of network traffic analysis are regression and classification. Previous work has previously selected flow and packet-level features for use with random forest regression. For network traffic data analysis, current classifiers such as SVM, KNN, Nave Bayes, and Random Forest are used.