Network classification for traffic management : anomaly detection, feature selection, clustering and classification /
Tari, Zahir,author.
Fahad, Adil,author.
Almalawi, Abdulmohsen,author.
Yi, Xun(College teacher),author.
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; transport layer statistics quality; feature set; privacy preserving framework for traffic data publishing; semi-supervised approach for network traffic labelling; and hybrid clustering-classification.
Includes bibliographical references and index.
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.
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; transport layer statistics quality; feature set; privacy preserving framework for traffic data publishing; semi-supervised approach for network traffic labelling; and hybrid clustering-classification.
Telecommunication
Computer network protocols