Artificial intelligence-driven traffic analysis and anomaly detection for telecommunication networks and internet of things devices

Abstract

Aspects of the subject disclosure may include, for example, receiving application traffic from a plurality of Internet of Things (IoT) devices processing an application, including receiving the application traffic over a mobile communication network, clustering the application traffic to identify clusters of similar IoT devices based on common characteristics of the application traffic, receiving unknown traffic over the mobile communication network, determining a closest cluster based on similarities between the unknown traffic and respective clusters of the clusters of IoT devices, decomposing traffic signals of the closest cluster into trend, period, and noise information, forming decomposed traffic, reconstructing the decomposed traffic into reconstructed traffic based on the trend information and the period information to remove noise information from the traffic signals of the closest cluster, forming a baseline for the closest cluster, detecting an anomaly in the reconstructed traffic based on a variation in data of the reconstructed traffic from data of the baseline for the closest cluster exceeding a statistical threshold and initiating a corrective action to limit a security threat based on the anomaly in the reconstructed traffic. Other embodiments are disclosed.