Network Classification for Traffic Management: Anomaly detection, feature selection, clustering and classification
By 作者: Abdulmohsen Almalawi, Adil Fahad, Xun Yi, Zahir Tari
pages 页数: 288 pages
Edition 版本: 1
Language 语言: English
Publisher Finelybook 出版社: The Institution of Engineering and Technology
Publication Date 出版日期: 2020-03-23
The Book Description robot was collected from Amazon and arranged by Finelybook
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.
Network Classification for Traffic Management 9781785619212.pdf