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 ...
Results of an experimental study of an anomaly detection system based on the paradigm of artificial immune systems (AISs) are presented. Network traffic data are mapped into ant...
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...
The problem of finding anomaly has received much attention recently. However, most of the anomaly detection algorithms depend on an explicit definition of anomaly, which may be i...
Ada Wai-Chee Fu, Oscar Tat-Wing Leung, Eamonn J. K...
This paper adresses the problem of anomaly detection and classification by using a noisy measurement vector corrupted by some linear unknown nuisance parameters. An invariant con...