Anomaly detection has recently been applied to various areas, and several techniques
based on deep learning have been proposed for the analysis of multivariate time series. In …

The industrial Internet of Things (IIoT) is the use of Internet of Things (IoT) technologies in
manufacturing which harnesses the machine data generated by various sensors and …

Detecting anomalies in telemetry data captured on-board a spacecraft is critical to ensure its
safe operation. Although there exist various techniques for automatically detecting point …

The field of time series anomaly detection is constantly advancing, with several methods
available, making it a challenge to determine the most appropriate method for a specific …

This paper presents a generic anomaly detection approach for time-series data. Existing
anomaly detection approaches have several drawbacks such as a large number of false …

It has been shown that deep learning models can under certain circumstances outperform
traditional statistical methods at forecasting. Furthermore, various techniques have been …

Anomaly Detection is widely used in applications related but not limited to intrusion
detection, fault detection, fraud detection, health monitoring systems and many other places …

For a fault detection of machine tools, fixed intervention thresholds are usually necessary. In
order to provide an autonomous anomaly detection without the need for fixed limits …

Application-layer protocols are widely adopted for signaling in telecommunication networks
such as the 5G networks. However, they can be subject to application-layer attacks that are …

Machine learning has vast potential to improve anomaly detection in satellite telemetry
which is a crucial task for spacecraft operations. This potential is currently hampered by a …