… of adaptive control charts to discover deviations in sequential estimates of statistics of
interest. Behaviour-based Anomaly Detection (BAD) involves learning and detecting changes in …

… To detect failures, we need … Adaptive Anomaly Detection (AAD) framework for cloud
dependability assurance. It employs data description using hypersphere for adaptive failure detection…

We address the problem of anomaly detection in videos. The goal is to identify unusual
behaviours automatically by learning exclusively from normal videos. Most existing approaches …

… We presented adaptive anomaly detectors for hyperspectral imagery that exploit the
spectral and spatial relationships within a local area. The Gaussian assumption for local data …

… proposed fast adaptive anomaly detection framework in details. In Section 3.1, we introduce
the adaptive EBM which consists of a deep feature extractor followed by an adaptive sparse …

… The main contribution of this paper is the proposal of an adaptive model based anomaly
detection system for ADL. This system adapts to new data corresponding to changes in the …

… Finally, our adaptive models outperform the statically generated ones retaining the gains in
… alleviate some of the challenges faced as anomaly detection is increasingly relied upon as a …

… The article presents an adaptive anomaly detection system for ICS which addresses …
detected anomalies as possible symptoms of cyber-attacks. The creation of the anomaly detection …

… and adaptive performance anomaly detection approach based … by identifying groups of
anomalous metric patterns, which … of online anomaly detection with and without the adaptive …

… adaptive end-host anomaly detector where a supervised classifier trained as a traffic predictor
is used to control a time-varying detection … , we show that our detector outperforms a fixed-…