In this work we consider the problem of monitoring information streams for anomalies in a scalable and efficient manner. We study the problem in the context of network streams wher...
Kernel functions as similarity measures for sequential data have been extensively studied in previous research. This contribution addresses the efficient computation of distance fu...
An outlier is an observation that deviates so much from other observations as to arouse suspicion that it was generated by a different mechanism. Outlier detection has many applic...
Detecting outliers is an important topic in data mining. Sometimes the outliers are more interesting than the rest of the data. Outlier identification has lots of applications, su...
— Anomaly-based intrusion detection systems have the ability of detecting novel attacks, but in real-time detection, they face the challenges of producing many false alarms and f...