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

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Network Classification for Traffic Management: Anomaly detection, feature selection, clustering and classification - Tari, Zahir, and Fahad, Adil, and Almalawi, Abdulmohsen
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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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Network Classification for Traffic Management: Anomaly detection, feature selection, clustering and classification 2020, Institution of Engineering and Technology, Stevenage

ISBN-13: 9781785619212

Hardcover