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- W1553257641 abstract "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." @default.
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- W1553257641 date "2008-09-17" @default.
- W1553257641 modified "2023-10-17" @default.
- W1553257641 title "Improving Anomaly Detection Error Rate by Collective Trust Modeling" @default.
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- W1553257641 doi "https://doi.org/10.1007/978-3-540-87403-4_25" @default.
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