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Intrusion detection system (IDS) research field has grown tremendously in the past decade. Improving the detection rate of user to root (U2R) attack classes is an open research problem. Current IDS uses all data features to detect intrusions. Some of the features may be redundant to the detection process. The purpose of this empirical study is to identify important features to improve the detection...
In this paper, a novel naïve Bayesian classifier based on the hybrid-weight feature attributes (short of "NBCHWFA") is proposed. NBCHWFA arranges a hybrid weight for each feature attribute by merging the effectiveness of feature attribute on classification and the dependence between feature attribute and class attribute. In order to demonstrate the feasibility and effectiveness of proposed...
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