Graduate School and Research Center in Digital Sciences

Hybrid traffic identification

Pietrzyk, Marcin; En-Najjary, Taoufik; Urvoy-Keller, Guillaume; Costeux, Jean-Laurent

Research Report RR-10-238

      Traffic classification is a key function for ISPs and companies in general. Several different classes of methods have been proposed, especially deep packet inspection (DPI) and machine learning based approaches. Each approach is in general efficient for some classes of applications. However, there is no one-fit-all method, i.e., no method that offers the best performance for all applications. In this paper, we propose a framework, called Hybrid Traffic Identification (HTI) that enables to take advantage of the merits of different approaches. Any source of information (flow statistics, signatures, etc) is encoded as a feature; the actual classification is made by a machine learning algorithm. We demonstrated that HTI is not-dependent on a specific machine learning algorithm, and that any classification method can be incorporated to HTI as its decision could be encoded as a new feature. Using multiple traces from a large ISP, we demonstrate that HTI outperforms state-of-the-art methods as it can select the best sources of information for each application to maximize its ability to detect it. We further report on an ongoing live experiment with our HTI instance in production network of the large ISP, which already represents several weeks of continual traffic classification.

Document Bibtex

Title:Hybrid traffic identification
Type:Report
Language:English
City:
Date:
Department:Digital Security
Eurecom ref:3075
Copyright: © EURECOM. Personal use of this material is permitted. The definitive version of this paper was published in Research Report RR-10-238 and is available at :
Bibtex: @techreport{EURECOM+3075, year = {2010}, title = {{H}ybrid traffic identification}, author = {{P}ietrzyk, {M}arcin and {E}n-{N}ajjary, {T}aoufik and {U}rvoy-{K}eller, {G}uillaume and {C}osteux, {J}ean-{L}aurent }, number = {EURECOM+3075}, month = {04}, institution = {Eurecom}, url = {http://www.eurecom.fr/publication/3075},, }
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