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@inproceedings{786656,
author = {Rehák, Martin and Pěchouček, Michal and Bartoš, Karel and Grill, Martin and Čeleda, Pavel and Krmíček, Vojtěch},
address = {Berlin},
booktitle = {Recent Advances in Intrusion Detection},
keywords = {network behavior analysis; trust modeling},
language = {eng},
location = {Berlin},
isbn = {978-3-540-87402-7},
pages = {398-399},
publisher = {Springer Berlin / Heidelberg},
title = {Improving Anomaly Detection Error Rate by Collective Trust Modeling},
year = {2008}
}
TY - JOUR
ID - 786656
AU - Rehák, Martin - Pěchouček, Michal - Bartoš, Karel - Grill, Martin - Čeleda, Pavel - Krmíček, Vojtěch
PY - 2008
TI - Improving Anomaly Detection Error Rate by Collective Trust Modeling
PB - Springer Berlin / Heidelberg
CY - Berlin
SN - 9783540874027
KW - network behavior analysis
KW - trust modeling
N2 - Current Network Behavior Analysis (NBA) techniques are based on anomaly detection principles and therefore subject to high error rates. We propose a mechanism that deploys trust modeling, a technique for cooperator modeling from the multi-agent research, to improve the quality of NBA results. Our system is designed as a set of agents, each of them based on an existing anomaly detection algorithm coupled with a trust model based on the same traffic representation. These agents minimize the error rate by unsupervised, multi-layer integration of traffic classification. The system has been evaluated on real traffic in Czech academic networks.
ER -
REHÁK, Martin, Michal PĚCHOUČEK, Karel BARTOŠ, Martin GRILL, Pavel ČELEDA a Vojtěch KRMÍČEK. Improving Anomaly Detection Error Rate by Collective Trust Modeling. In \textit{Recent Advances in Intrusion Detection}. Berlin: Springer Berlin / Heidelberg, 2008, s.~398-399. ISBN~978-3-540-87402-7.
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