Incremental Stream Clustering for Anomaly Detection and Classification

We have designed a framework for Bayesian Statistical Anomaly Detection, called ISC, or Incremental Stream Clustering. It learns the normal situation incrementally, and can on the fly detect anomalous cases. When this happens, a new cluster can be created, so similar cases can be detected in the future. In this way, the framework performs incremental clustering, while at the same time either classifying a new case as belonging to one of the known clusters or indicating that it is from a previously unseen situation.