Network classification for traffic management : anomaly detection, feature selection, clustering and classification

The book investigates network traffic classification solutions by proposing transport-layer methods to achieve better run and operated enterprise-scale networks. It deals with the following subjects: traffic management; anomaly detection; clustering algorithms; unsupervised feature selection; transp...

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Bibliographic Details
Main Authors Tari, Zahir, 1961- (Author), Fahad, Adil (Author), Almalawi, Abdulmohsen (Author), Yi, Xun (College teacher) (Author)
Format Electronic eBook
LanguageEnglish
Published Stevenage : Institution of Engineering and Technology, 2020.
SeriesIET computing series ; 32.
Subjects
Telecommunication > Traffic > Management.
Computer network protocols > Management.
elektronické knihy
electronic books
Online AccessFull text
ISBN1785619225
9781785619229
1785619217
9781785619212
Physical Description1 online resource : illustrations

Cover

Table of Contents:
  • Introduction
  • Background
  • Related work
  • A taxonomy and empirical analysis of clustering algorithms for traffic classification
  • Toward an efficient and accurate unsupervised feature selection
  • Optimizing feature selection to improve transport layer statistics quality
  • Optimality and stability of feature set for traffic classification
  • A privacy-perserving framework for traffic data publishing
  • A semi-supervised approach for network traffic labeling
  • A hybrid clustering-classification for accurate and efficient network classification
  • Conclusion.

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