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dc.contributor.authorCarela Español, Valentín
dc.contributor.authorBujlow, Tomasz
dc.contributor.authorBarlet Ros, Pere
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
dc.date.accessioned2014-06-17T12:23:33Z
dc.date.created2014
dc.date.issued2014
dc.identifier.citationCarela, V.; Bujlow, T.; Barlet, P. Is our ground-truth for traffic classification reliable?. A: Passive and Active Measurment Conference. "Passive and Active Measurement: 15th International Conference, PAM 2014: Los Angeles, CA, USA: March 10-11, 2014: proceedings". Los Ángeles, CA: 2014, p. 98-108.
dc.identifier.isbn978-3-319-04917-5
dc.identifier.urihttp://hdl.handle.net/2117/23246
dc.description.abstractThe validation of the different proposals in the traffic classification literature is a controversial issue. Usually, these works base their results on a ground-truth built from private datasets and labeled by techniques of unknown reliability. This makes the validation and comparison with other solutions an extremely difficult task. This paper aims to be a first step towards addressing the validation and trustworthiness problem of network traffic classifiers. We perform a comparison between 6 well-known DPI-based techniques, which are frequently used in the literature for ground-truth generation. In order to evaluate these tools we have carefully built a labeled dataset of more than 500 000 flows, which contains traffic from popular applications. Our results present PACE, a commercial tool, as the most reliable solution for ground-truth generation. However, among the open-source tools available, NDPI and especially Libprotoident, also achieve very high precision, while other, more frequently used tools (e.g., L7-filter) are not reliable enough and should not be used for ground-truth generation in their current form.
dc.format.extent11 p.
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors
dc.subjectÀrees temàtiques de la UPC::Informàtica::Seguretat informàtica
dc.subject.lcshNeural networks (Computer science)
dc.subject.lcshComputer security
dc.subject.otherCommercial tools
dc.subject.otherL7 filters
dc.subject.otherLabeled dataset
dc.subject.otherNetwork traffic
dc.subject.otherOpen source tools
dc.subject.otherTraffic classification
dc.titleIs our ground-truth for traffic classification reliable?
dc.typeConference report
dc.subject.lemacOrdinadors, Xarxes d'
dc.subject.lemacSeguretat informàtica
dc.contributor.groupUniversitat Politècnica de Catalunya. CBA - Sistemes de Comunicacions i Arquitectures de Banda Ampla
dc.identifier.doi10.1007/978-3-319-04918-2-10
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://link.springer.com/chapter/10.1007%2F978-3-319-04918-2_10
dc.rights.accessRestricted access - publisher's policy
drac.iddocument14916091
dc.description.versionPostprint (published version)
dc.date.lift10000-01-01
upcommons.citation.authorCarela, V.; Bujlow, T.; Barlet, P.
upcommons.citation.contributorPassive and Active Measurment Conference
upcommons.citation.pubplaceLos Ángeles, CA
upcommons.citation.publishedtrue
upcommons.citation.publicationNamePassive and Active Measurement: 15th International Conference, PAM 2014: Los Angeles, CA, USA: March 10-11, 2014: proceedings
upcommons.citation.startingPage98
upcommons.citation.endingPage108


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Except where otherwise noted, content on this work is licensed under a Creative Commons license: Attribution-NonCommercial-NoDerivs 3.0 Spain