Abstract: Examples of the disclosure enable detecting an anomalous state in a machine. The method is performed by an anomaly detection server. The method includes receiving training analysis vectors associated with a monitored machine during a training period. The method also includes applying the training analysis vectors to a machine learning model to create a trained machine learning model configured to describe normal states in the monitored machine as indicated by training analysis vectors. The method further includes receiving monitoring analysis vectors associated with the monitored machine during a monitoring period. The method also includes applying the monitoring analysis vectors to the trained machine learning model to identify at least one discrepancy indicating an anomalous state in the monitored machine. The method further includes transmitting an alert indicating that an anomaly is detected in the monitored machine.

Abstract: Examples of the disclosure enable detecting an anomalous state in a machine. The method is performed by an anomaly detection server. The method includes receiving training analysis vectors associated with a monitored machine during a training period. The method also includes applying the training analysis vectors to a machine learning model to create a trained machine learning model configured to describe normal states in the monitored machine as indicated by training analysis vectors. The method further includes receiving monitoring analysis vectors associated with the monitored machine during a monitoring period. The method also includes applying the monitoring analysis vectors to the trained machine learning model to identify at least one discrepancy indicating an anomalous state in the monitored machine. The method further includes transmitting an alert indicating that an anomaly is detected in the monitored machine.