For example, behavioral analytics with anomaly detection is helping to identify subtle context-based anomalies. This approach looks at not just individual data points but the broader context of user ...

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In this paper, we developed a system called AADDS: an Autoencoder-based Anomaly Detection for the DoH traffic System consists of Traffic Capture module and Anomaly Detection module. The Traffic ...

This paper proposes CAE-AD, a novel convolutional autoencoder anomaly detection method that relies only on normal operation data for training the intelligent classi-fier. The method also accommodates ...

As chemical processes become increasingly digitized and data-rich, the need for intelligent, structure-aware anomaly detection methods has never been more critical. This Research Topic aims to bring ...