Pattern Recognition Approaches for Classifying IP Flows

Authors:
Alice Este;Francesco Gargiulo;Francesco Gringoli;Luca Salgarelli;Carlo Sansone
Affiliations:
DEA, Università degli Studi di Brescia, Brescia, Italy 25123;Dipartimento di Informatica e Sistemistica, Università degli Studi di Napoli Federico II, Napoli, Italy I-80125;DEA, Università degli Studi di Brescia, Brescia, Italy 25123;DEA, Università degli Studi di Brescia, Brescia, Italy 25123;Dipartimento di Informatica e Sistemistica, Università degli Studi di Napoli Federico II, Napoli, Italy I-80125
Venue:
SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Year:
2008

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Abstract

The assignment of an IP flow to a class, according to the application that generated it, is at the basis of any modern network management platform. However, classification techniques such as the ones based on the analysis of transport layer or application layer information are rapidly becoming ineffective. Moreover, in several network scenarios it is quite unrealistic to assume that all the classes an IP flow can belong to are a priori known. In these cases, in fact, some network protocols may be known, but novel protocols can appear so giving rise to unknown classes. In this paper we propose to face the problem of classifying IP flows by means of different pattern recognition approaches. They have been explicitly devised in order to effectively address the problem of the unknown classes, too. An experimental evaluation of the various proposal on real traffic traces is also provided, by considering different network scenarios.