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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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Tari, Zahir, 1961- (Autor), Fahad, Adil (Autor), Almalawi, Abdulmohsen (Autor), Yi, Xun (College teacher) (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Stevenage : Institution of Engineering and Technology, 2020.
Colección:IET computing series ; 32.
Temas:
Telecommunication > Traffic > Management.
Computer network protocols > Management.
Télécommunications > Trafic > Gestion.
Protocoles de réseaux d'ordinateurs > Gestion.
Telecommunication > Traffic > Management
computer network management.
computer network security.
data privacy.
feature selection.
learning (artificial intelligence)
pattern classification.
pattern clustering.
telecommunication traffic.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • 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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