Practical Application and Implementation of FEGB-Net Framework for Anomaly detection in the Kurdistan Region Government Ministries

<jats:p>&lt;p&gt;This paper presents the deployment and application of the Federated Ensemble Graph-Based Network (FEGB-Net) framework within the Kurdistan Region Government (KRG) ministries. The system integrates Federated Learning (FL), Graph Neural Networks (GNNs), and ensemble machine learning to provide privacy-preserving and collaborative anomaly detection in distributed government networks. Real-world deployment across key ministries demonstrated improved detection accuracy (97.6 %), low false-positive rates (3.2 %), and enhanced resilience against adversarial and stealthy attacks, while maintaining full compliance with governmental data-sovereignty requirements.&lt;/p&gt;</jats:p>