Anomaly Detection for 5G Softwarized Infrastructures with Federated Learning

Abstract

We present how to distribute an anomaly detection framework at the state of the art, called SYRROCA (SYstem Radiography and ROot Cause Analysis), for edge computing and 5G environment, using federated learning. The goal is to leverage on the distributed nature of federated learning to support data locality and local training of artificial intelligence modules, such as anomaly detection modules needed for closed-loop automation systems. We describe how the different functional modules interact and can be demonstrated.