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Network Classification for Traffic Management: Anomaly detection, feature selection, clustering and classification

by Zahir Tari, Adil Fahad, Abdulmohsen Almalawi and Xun Yi
The Institution of Engineering and Technology, 2020
Cloth: 978-1-78561-921-2 | eISBN: 978-1-83724-639-7 (ePub) | eISBN: 978-1-78561-922-9 (PDF)

ABOUT THIS BOOK

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.
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