The custom, ad hoc nature of web applications makes learning-based anomaly detection systems a suitable approach to provide early warning about the exploitation of novel vulnerabi...
William K. Robertson, Giovanni Vigna, Christopher ...
In this paper, we describe disparity, a tool that does parallel, scalable anomaly detection for clusters. Disparity uses basic statistical methods and scalable reduction operation...
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 ...
Anomaly detection is a pattern recognition task whose goal is to report the occurrence of abnormal or unknown behavior in a given system being monitored. In this paper we propose a...
Rewbenio A. Frota, Guilherme De A. Barreto, Jo&ati...
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...