About: Towards Efficient Flow Sampling Technique for Anomaly Detection

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
rdfs:seeAlso	http://www.springerlink.com/content/aht28428hmm47366/fulltext.pdf
Description	With increasing amount of network traffic, sampling techniques have become widely employed allowing monitoring and analysis of high-speed network links. Despite of all benefits, sampling methods negatively influence the accuracy of anomaly detection techniques and other subsequent processing. In this paper, we present an adaptive, feature-aware sampling technique that reduces the loss of information bounded with the sampling process, thus minimizing the decrease of anomaly detection efficiency. To verify the optimality of our proposed technique, we build a model of the ideal sampling algorithm and define general metrics allowing us to compute the distortion of traffic feature distribution for various types of sampling algorithms. We compare our technique with random flow sampling and reveal their impact on several anomaly detection methods by using real network traffic data. The presented ideas can be applied on high-speed network links to refine the input data by suppressing highly-redundant information. With increasing amount of network traffic, sampling techniques have become widely employed allowing monitoring and analysis of high-speed network links. Despite of all benefits, sampling methods negatively influence the accuracy of anomaly detection techniques and other subsequent processing. In this paper, we present an adaptive, feature-aware sampling technique that reduces the loss of information bounded with the sampling process, thus minimizing the decrease of anomaly detection efficiency. To verify the optimality of our proposed technique, we build a model of the ideal sampling algorithm and define general metrics allowing us to compute the distortion of traffic feature distribution for various types of sampling algorithms. We compare our technique with random flow sampling and reveal their impact on several anomaly detection methods by using real network traffic data. The presented ideas can be applied on high-speed network links to refine the input data by suppressing highly-redundant information. (en)
Title	Towards Efficient Flow Sampling Technique for Anomaly Detection Towards Efficient Flow Sampling Technique for Anomaly Detection (en)
skos:prefLabel	Towards Efficient Flow Sampling Technique for Anomaly Detection Towards Efficient Flow Sampling Technique for Anomaly Detection (en)
skos:notation	RIV/68407700:21230/12:00191018!RIV13-MSM-21230___
http://linked.open...avai/predkladatel	Fakulta elektrotechnická
http://linked.open...avai/riv/aktivita	P S
http://linked.open...avai/riv/aktivity	P(ME10051), P(VG20122014079), S
http://linked.open...vai/riv/dodaniDat	2013
http://linked.open...aciTvurceVysledku	Rehák, Martin Bartoš, Karel
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	České vysoké učení technické v Praze / Fakulta elektrotechnická
http://linked.open...dnocenehoVysledku	174707
http://linked.open...ai/riv/idVysledku	RIV/68407700:21230/12:00191018
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	sampling; anomaly detection; NetFlow; intrusion detection (en)
http://linked.open.../riv/klicoveSlovo	NetFlow intrusion detection sampling anomaly detection
http://linked.open...ontrolniKodProRIV	[160C31B5F1C1]
http://linked.open...v/mistoKonaniAkce	Vienna
http://linked.open...i/riv/mistoVydani	Berlin
http://linked.open...i/riv/nazevZdroje	Traffic Monitoring and Analysis
http://linked.open...in/vavai/riv/obor	JC
http://linked.open...ichTvurcuVysledku	2 (xsd:int)
http://linked.open...cetTvurcuVysledku	2 (xsd:int)
http://linked.open...vavai/riv/projekt	Behavioral Detection of Advanced Persistent Threats in Computer Networks AnomalyNET: Anomaly detection enhanced honeypots
http://linked.open...UplatneniVysledku	2012
http://linked.open...iv/tvurceVysledku	Bartoš, Karel Rehák, Martin
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2012-03-12 (xsd:date)
issn	0302-9743
number of pages	14 (xsd:int)
http://bibframe.org/vocab/doi	10.1007/978-3-642-28534-9_11
http://purl.org/ne...btex#hasPublisher	Springer-Verlag
https://schema.org/isbn	978-3-642-28533-2
http://localhost/t...ganizacniJednotka	21230
is http://linked.open...avai/riv/vysledek of	Towards Efficient Flow Sampling Technique for Anomaly Detection

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