Machine Learning Based Network Attacks Classification
Yuxuan Che · 2023
Nowadays, the rapidly growing internet also brings more and more network attacks. Such attacks seriously affect normal activities and threaten individual privacy. Applying machine learning approaches makes the detection and response to network attacks faster and effective. In this paper, it aims to review many of the individual researches and looks forward to future changes and modifications based on existing model. In this paper, it collects and analyzes many previous researches utilizing Naïve Bayes and SVM (Support Vector Machine) approaches in detection to network attacks. Starting from basic data processing to the detailed explanations of each research and its result, this paper compares their differences and similarities. In this paper, it also discusses the introduction to Naïve Bayes classifier, SVM classifier, and fundamental concepts involving in result analysis. In the end of this paper, it also summarizes the overall machine learning application on network attack detection, and looks forward to the future.