US Patent 11689944 Traffic flow classification using machine learning

Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for traffic flow classification using machine learning. In some implementations, a communication device includes an anomaly detector comprising a machine learning model trained to predict whether data traffic patterns differ from a set of observed traffic patterns present in a set of training data. The communication device includes a traffic classifier comprising a machine learning model trained to predict a quality of service (QoS) class for network connections or data flows. The communication device is configured to evaluate network connections or data flows using the anomaly detector. The communication device may (i) use the traffic classifier to predict QoS classes for traffic that the anomaly detector predicts to be similar to the observed traffic patterns, and (ii) store data traffic that the anomaly detector predicts to be different from the observed traffic patterns.