n the last years network traffic classification has attracted much research effort, given that it represents the foundation of many Internet functionalities such as Quality of Service (QoS) enforcement, monitoring, and security. Nonetheless, the proposed works are not able to satisfactorily solve the problem, usually being suitable for only addressing a given portion of the whole network traffic and thus none of them can be considered an ultimate solution for network classification. In this paper, we address network traffic classification by proposing a new architecture - named Waterfall architecture - that, by combining several classification algorithms together according to a cascade principle, is able to correctly classify the whole mixture of network traffic. Through extensive experimental tests run over real traffic datasets, we have demonstrated the effectiveness of the proposal.

Waterfall: rapid identification of IP flows using cascade classification

CALLEGARI, CHRISTIAN;PAGANO, MICHELE
2014-01-01

Abstract

n the last years network traffic classification has attracted much research effort, given that it represents the foundation of many Internet functionalities such as Quality of Service (QoS) enforcement, monitoring, and security. Nonetheless, the proposed works are not able to satisfactorily solve the problem, usually being suitable for only addressing a given portion of the whole network traffic and thus none of them can be considered an ultimate solution for network classification. In this paper, we address network traffic classification by proposing a new architecture - named Waterfall architecture - that, by combining several classification algorithms together according to a cascade principle, is able to correctly classify the whole mixture of network traffic. Through extensive experimental tests run over real traffic datasets, we have demonstrated the effectiveness of the proposal.
2014
Foremski, Paweł; Callegari, Christian; Pagano, Michele
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/759894
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 14
  • ???jsp.display-item.citation.isi??? 15
social impact