Learning Rules for Anomaly Detection

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Google Tech Talks
August 10, 2007

ABSTRACT

Anomaly detection has the potential to detect novel attacks, however, keeping the false alarm rate low is a challenging task. We discuss the LERAD algorithm that can learn concise and accurate rules for anomaly detection and demonstrate its effectiveness in network and host datasets. We will also discuss our recent work (KDD 07) on weighting versus pruning during the rule validation.

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