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Description
  • Current network intrusion detection methods based on anomaly detection approaches suffer from comparatively higher error rate and low performance. Proposed flow based network intrusion detection system addresses these issues by (i) using hardware-accelerated probes to collect unsampled NetFlow data from gigabit-speed network links and (ii) combining several anomaly detection algorithms by means of collective trust modeling, a multi-agent data fusion method. The data acquired on the network is preprocessed and passed to anomaly detection models to gather independent anomaly opinions for each flow. The anomaly data is passed to several trust models to aggregate the anomalies with past experience, and the flows are re-evaluated to obtain their trustfulness, which is further aggregated to detect malicious traffic. Experiments performed on-line on real campus network illustrate system suitability for real-time network surveillance.
  • Current network intrusion detection methods based on anomaly detection approaches suffer from comparatively higher error rate and low performance. Proposed flow based network intrusion detection system addresses these issues by (i) using hardware-accelerated probes to collect unsampled NetFlow data from gigabit-speed network links and (ii) combining several anomaly detection algorithms by means of collective trust modeling, a multi-agent data fusion method. The data acquired on the network is preprocessed and passed to anomaly detection models to gather independent anomaly opinions for each flow. The anomaly data is passed to several trust models to aggregate the anomalies with past experience, and the flows are re-evaluated to obtain their trustfulness, which is further aggregated to detect malicious traffic. Experiments performed on-line on real campus network illustrate system suitability for real-time network surveillance. (en)
Title
  • Flow Based Network Intrusion Detection System using Hardware-Accelerated NetFlow Probes
  • Flow Based Network Intrusion Detection System using Hardware-Accelerated NetFlow Probes (en)
skos:prefLabel
  • Flow Based Network Intrusion Detection System using Hardware-Accelerated NetFlow Probes
  • Flow Based Network Intrusion Detection System using Hardware-Accelerated NetFlow Probes (en)
skos:notation
  • RIV/00216224:14610/08:00042091!RIV11-MSM-14610___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(1M0567), V, Z(MSM6383917201), Z(MSM6840770038)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 368199
http://linked.open...ai/riv/idVysledku
  • RIV/00216224:14610/08:00042091
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • network intrusion detection; anomaly detection; security; NetFlow (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [D5066A11BDA4]
http://linked.open...v/mistoKonaniAkce
  • Prague
http://linked.open...i/riv/mistoVydani
  • Prague
http://linked.open...i/riv/nazevZdroje
  • CESNET Conference 2008 : security, middleware, and virtualization – glue of future networks
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Čeleda, Pavel
  • Krmíček, Vojtěch
  • Bartoš, Karel
  • Grill, Martin
  • Rehák, Martin
http://linked.open...vavai/riv/typAkce
http://linked.open...ain/vavai/riv/wos
  • 000271023300006
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
http://purl.org/ne...btex#hasPublisher
  • CESNET, z. s. p. o
https://schema.org/isbn
  • 978-80-904173-0-4
http://localhost/t...ganizacniJednotka
  • 14610
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