International Journal of Information and Communication Technology Research (IJICT، جلد ۱۴، شماره ۲، صفحات ۱-۱۳
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عنوان انگلیسی A Review on Internet Traffic Classification Based on Artificial Intelligence Techniques
چکیده انگلیسی مقاله 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.
کلیدواژه‌های انگلیسی مقاله Internet Traffic Classification, Network Traffic Analysis, DL, ML, Artificial intelligence
نویسندگان مقاله | Mohammad Pooya Malek
Telecommunications Department Broadcast University (IRIBU) Tehran, Iran


| Shaghayegh Naderi
ICT Research Institute (ITRC) Tehran, Iran


| Hossein Gharaee Garakani
ICT Research Institute (ITRC) Tehran, Iran
نشانی اینترنتی http://ijict.itrc.ac.ir/browse.php?a_code=A-10-4391-1&slc_lang=en&sid=1
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