Passive local network monitoring using Zeek packet extraction and machine learning

Standard residential firewalls rely on static blacklists and simple DNS blocking. To build a true lightweight local edge ai cybersecurity appliance for residential network security, you need to bring machine learning inference directly to the physical network boundary.

The XGBoost Framework

EdgeDefenseAI utilizes XGBoost binary classification model parameters for network anomaly traffic detection. By parsing real-time packet headers via Zeek, the model evaluates flow duration, payload entropy, and destination ASN velocity to flag irregular telemetry payloads without requiring heavy computational resources or cloud connectivity.