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Performance evaluation of classification and feature selection algorithms for NetFlow-based protocol recognition

dc.contributor.authorAbt, Sebastian
dc.contributor.authorWener, Sascha
dc.contributor.authorBaier, Harald
dc.contributor.editorHorbach, Matthias
dc.date.accessioned2019-03-07T09:31:44Z
dc.date.available2019-03-07T09:31:44Z
dc.date.issued2013
dc.description.abstractProtocol recognition is a commonly required technique to deploy servicedependent billing schemes and to secure computer networks, e.g., to reliably determine the protocol used for a botnet command and control (C & C) channel. In the past, different deep packet inspection based approaches to protocol recognition have been proposed. However, such approaches suffer from two drawbacks: first, they fail when data streams are encrypted, and second, they do not scale at high traffic rates. To overcome these limitations, in this paper we evaluate the performance in terms of precision and recall (i.e., accuracy) of different feature selection and classification algorithms with regard to NetFlow-based protocol recognition. As NetFlow does not rely on payload information and gives a highly aggregated view on network communication, it serves as a natural data source in ISP networks. Our evaluation shows that NetFlow based protocol detection achieves high precision and recall rates of more than 92% for widespread protocols used for C&C communication (e.g., HTTP, DNS).en
dc.identifier.isbn978-3-88579-614-5
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/20648
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofINFORMATIK 2013 – Informatik angepasst an Mensch, Organisation und Umwelt
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-220
dc.titlePerformance evaluation of classification and feature selection algorithms for NetFlow-based protocol recognitionen
dc.typeText/Conference Paper
gi.citation.endPage2197
gi.citation.publisherPlaceBonn
gi.citation.startPage2184
gi.conference.date16.-20. September 2013
gi.conference.locationKoblenz
gi.conference.sessiontitleRegular Research Papers

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