This paper presents a robust unsupervised learning approach for detection of anomalies in patterns of human behavior using multi-modal smart environment sensor data. We model the ...
We present an architecture1 designed for alert verification (i.e., to reduce false positives) in network intrusion-detection systems. Our technique is based on a systematic (and a...
Mining for outliers in sequential databases is crucial to forward appropriate analysis of data. Therefore, many approaches for the discovery of such anomalies have been proposed. ...
We have developed a method that can discriminate anomalous image sequences for more efficiently utilizing security videos. To match the wide popularity of security cameras, the me...
Embedded systems are being deployed as a part of critical infrastructures and are vulnerable to malicious attacks due to internet accessibility. Intrusion detection systems have b...
Tao Zhang, Xiaotong Zhuang, Santosh Pande, Wenke L...