Название: Network Classification for Traffic Management: Anomaly detection, feature selection, clustering and classification
Автор: Zahir Tari, Adil Fahad
Издательство: The Institution of Engineering and Technology
Год: 2020
Страниц: 276
Язык: английский
Формат: pdf (true), epub
Размер: 10.7 MB
With the massive increase of data and traffic on the Internet within the 5G, IoT and smart cities frameworks, current network classification and analysis techniques are falling short. Novel approaches using machine learning algorithms are needed to cope with and manage real-world network traffic, including supervised, semi-supervised, and unsupervised classification techniques. Accurate and effective classification of network traffic will lead to better quality of service and more secure and manageable networks. This authored book investigates network traffic classification solutions by proposing transport-layer methods to achieve better run and operated enterprise-scale networks.