Edge-based machine learning for encoding legitimate scanning

Abstract

In one embodiment, a device in a network receives an indication that a network anomaly detected by an anomaly detector of a first node in the network is associated with scanning activity in the network. The device receives labeled traffic data associated with the detected anomaly that identifies whether the traffic data is associated with legitimate or illegitimate scanning activity. The device trains a machine learning-based classifier using the labeled traffic data to distinguish between legitimate and illegitimate scanning activity in the network. The device deploys the trained classifier to the first node, to distinguish between legitimate and illegitimate scanning activity in the network.