 Anomalies are also referred to as outliers, novelties, noise, deviations and exceptions.In particular, in the context of abuse and network intrusion detection, the interesting objects are often not "rare" objects, but unexpected "bursts" in activity.This pattern does not adhere to the common statistical definition of an outlier as a rare object, and many outlier detection methods (in particular unsupervised methods) will fail on such data, unless it has been aggregated appropriately.