This authored book investigates network traffic classification solutions by proposing transport-layer methods to achieve better run and operated enterprise-scale networks.

Zahir Tari is a full professor and discipline head of the School of Computer Science, RMIT University, Australia. His expertise is in the areas of system performance (e.g., cloud, IoT) as well as system security (e.g., SCADA, cloud).

• Chapter 1: Introduction


• Chapter 2: Background


• Chapter 3: Related work


• Chapter 4: A taxonomy and empirical analysis of clustering algorithms for traffic classification


• Chapter 5: Toward an efficient and accurate unsupervised feature selection


• Chapter 6: Optimizing feature selection to improve transport layer statistics quality


• Chapter 7: Optimality and stability of feature set for traffic classification


• Chapter 8: A privacy-preserving framework for traffic data publishing


• Chapter 9: A semi-supervised approach for network traffic labeling


• Chapter 10: A hybrid clustering-classification for accurate and efficient network classification


• Chapter 11: Conclusion