Systems and methods for detecting beaconing communications using machine learning techniques

Abstract

A computerized method is disclosed that includes operations of obtaining network traffic data between a source device and a destination device, applying a set of one or more security rules to a plurality of metrics of the network traffic data to obtain a subset of network traffic metrics, applying a first trained machine learning model to the subset of network traffic metrics to generate a feature vector through feature extraction of the subset of network traffic metrics, and evaluate the feature vector for a presence of beaconing and classify the subset of network traffic metrics, and responsive to the classifying of the subset of network traffic metrics, generating a flag for a system administrator. The plurality of metrics include at least one or more of packet size, packet transmission rate, or a ratio of (i) packet size for inbound packets and (ii) packet size for outbound packets.