Volume 14, Issue 2 (6-2022)                   itrc 2022, 14(2): 1-13 | Back to browse issues page

XML Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Malek M P, Naderi S, Gharaee Garakani H. A Review on Internet Traffic Classification Based on Artificial Intelligence Techniques. itrc 2022; 14 (2) :1-13
URL: http://ijict.itrc.ac.ir/article-1-521-en.html
1- Telecommunications Department Broadcast University (IRIBU) Tehran, Iran
2- ICT Research Institute (ITRC) Tehran, Iran , Naderi@ITRC.ac.ir
3- ICT Research Institute (ITRC) Tehran, Iran
Abstract:   (501 Views)
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 5G 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 4th 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 140 identical researches. We then analyze the results and visualize a practical way of classifying internet traffic for popular applications.
Full-Text [PDF 1161 kb]   (597 Downloads)    
Type of Study: Research | Subject: Network

Add your comments about this article : Your username or Email:

Send email to the article author

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.