A Review on Internet Traffic Classification Based on Artificial Intelligence Techniques

Almost every industry has revolutionized with Artificial Intelligence. The telecommunication industry is one of them to improve customers' Quality of Services and Quality of Experience by enhancing networking infrastructure capabilities which could lead to much higher rates even in ۵G Networks. To this end, network traffic classification methods for identifying and classifying user behavior have been used. Traditional analysis with Statistical-Based, Port-Based, Payload-Based, and Flow-Based methods was the key for these systems before the ۴th industrial revolution. AI combination with such methods leads to higher accuracy and better performance. In the last few decades, numerous studies have been conducted on Machine Learning and Deep Learning, but there are still some doubts about using DL over ML or vice versa. This paper endeavors to investigate challenges in ML/DL use-cases by exploring more than ۱۴۰ identical researches. We then analyze the results and visualize a practical way of classifying internet traffic for popular applications.

کلیدواژه ها:

Internet Traffic Classification ، Network Traffic Analysis ، DL ، ML ، Artificial intelligence