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Intrusion detection systems (IDSs) must be capable of detecting new and unknown attacks, or anomalies. We study the problem of building detection models for both pure anomaly detection and combined misuse and anomaly detection (i.e., detection of both known and unknown intrusions). We show the necessity of artificial anomalies by discussing the failure to use conventional inductive learning methods...
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