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Books > Computing & IT > Computer communications & networking
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Network Classification for Traffic Management - Anomaly detection, feature selection, clustering and classification (Hardcover)
Loot Price: R3,196
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Network Classification for Traffic Management - Anomaly detection, feature selection, clustering and classification (Hardcover)
Series: Computing and Networks
Expected to ship within 10 - 15 working days
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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. This authored book investigates network traffic
classification solutions by proposing transport-layer methods to
achieve better run and operated enterprise-scale networks. The
authors explore novel methods for enhancing network statistics at
the transport layer, helping to identify optimal feature selection
through a global optimization approach and providing automatic
labelling for raw traffic through a SemTra framework to maintain
provable privacy on information disclosure properties.
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