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Detecting clusters of anomalies on low-dimensional feature subsets with application to network traffic flow data

Detecting clusters of anomalies on low-dimensional feature subsets with application to network traffic flow data

In a variety of applications, one desires to detect groups of anomalous data samples, with a group potentially manifesting its atypicality (relative to a reference model) on a low-dimensional subset of the full measured set of features. Samples may only be weakly atypical individually, whereas they may be strongly atypical …