An Unsupervised Network Intrusion Detection Based on Anomaly Analysis

Abstract

In this paper, an novel unsupervised intrusion detection method is presented, in which the anomalies was specified by choosing a reference measure μ which determines a density and a level value ρ. In order to reveal the relationship between the distribution of connection feature data sets and the reference measure μ, we proposed a new… (More)

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