We propose a new method for detecting patterns of anomalies in categorical datasets. We assume that anomalies are generated by some underlying process which affects only a particu...
Many works have been proposed on detecting individual anomalies in crowd scenes, i.e., human behaviors anomalous with respect to the rest of the behaviors. In this paper, we intro...
A new emerging paradigm of Uncertain Risk of Suspicion, Threat and Danger, observed across the field of information security, is described. Based on this paradigm a novel approac...
Most current network intrusion detection systems employ signature-based methods or data mining-based methods which rely on labelled training data. This training data is typically ...
Abstract: Fusion of information from graph features and content can provide superior inference for an anomaly detection task, compared to the corresponding content-only or graph fe...
John Grothendieck, Carey E. Priebe, Allen L. Gorin