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A Survey of Network Traffic Classification Methods Using Machine Learningстатья Перевод Электронная публикация
- Авторы: Getman A.I., Ikonnikova M.K.
- Журнал: Programming and Computer Software
- Том: 48
- Номер: 7
- Год издания: 2022
- Издательство: Pleiades Publishing, Ltd
- Местоположение издательства: Road Town, United Kingdom
- Первая страница: 413
- Последняя страница: 423
- DOI: 10.1134/s0361768822070052
- Аннотация: This survey is devoted to the task of network traffic classification, specifically, to the use of machine learning algorithms in this task. The survey begins with the description of the task, its different statements, and possible real-world applications. It then proceeds to the description of the methods historically used for network traffic classification, as well as their limitations and evolution of traffic making machine learning, which is the main way to solve the problem. The most popular machine learning algorithms used in this task are described and accompanied with examples of research papers that provide insight into their advantages and disadvantages. The problem of feature selection is discussed with subsequent consideration of a more global problem of acquiring a suitable dataset for network traffic classification; examples of popular datasets and their descriptions are provided. The paper concludes with an overview of some current problems in this field of research: model training and comparison, user data protection, and network traffic volatility.
- Добавил в систему: Гетьман Александр Игоревич