Autoencoder-based SCADA Telemetry Anomaly Detection This project implements an autoencoder-based anomaly detection system for SCADA (Supervisory Control and Data Acquisition) telemetry data. The ...

In this work, we propose an unsupervised anomaly clustering method leveraging a cyclic alignment-based offset detection algorithm for multivariate time-series signals. The proposed method is applied ...

This work aims at analyzing how provenance data can be used in anomaly detection by employing autoencoder networks which is a crucial operation for securing the various sectors through validation of ...

Get Code Download Data anomaly detection is the process of examining a set of source data to find data items that are different in some way from the majority of the source items. There are many ...

In the rapidly evolving landscape of 5G networks, effective anomaly detection is becoming increasingly important to ensure network stability and security. Traditional methods often encounter issues ...

It was also used for unsupervised sound anomaly detection to detect unknown abnormal sounds without abnormal sound training data (19). Recently, the autoencoder has been increasingly investigated in ...

Under the assumption that collider data can be modeled sufficiently adequately, we can employ the SM expectation to identify regions where measurements do not follow the SM expectation. This anomaly ...