Low Power Unsupervised Anomaly Detection by Nonparametric Modeling of Sensor Statistics

Nonparametric Spectral-Spatial Anomaly Detection

Due to abundant spectral information contained in the hyperspectral images, they are suitable data for anomalous targets detection. The use of spatial features in addition to spectral ones can improve the anomaly detection performance. An anomaly detector, called nonparametric spectral-spatial detector (NSSD), is proposed in this work which utilizes the benefits of spatial features and local st...

Unsupervised, low latency anomaly detection of algorithmically generated domain names by generative probabilistic modeling

We propose a method for detecting anomalous domain names, with focus on algorithmically generated domain names which are frequently associated with malicious activities such as fast flux service networks, particularly for bot networks (or botnets), malware, and phishing. Our method is based on learning a (null hypothesis) probability model based on a large set of domain names that have been whi...

Modeling Local Video Statistics for Anomaly Detection

MODELING LOCAL VIDEO STATISTICS FOR ANOMALY DETECTION

Unsupervised topic discovery by anomaly detection

Unsupervised Anomaly Detection

This paper describes work on the detection of anomalous material in text. We show several variants of an automatic technique for identifying an 'unusual' segment within a document, and consider texts which are unusual because of author, genre [Biber, 1998], topic or emotional tone. We evaluate the technique using many experiments over large document collections, created to contain randomly inse...