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Modelling and Data Analysis
2026. Vol. 16, no. 1, 50–60
doi:10.17759/mda.2026160103
ISSN: 2219-3758 / 2311-9454 (online)

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

 
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Abstract

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.

General Information

Keywords: machine learning, intrusion detection system (IDS), Federated Learning (FL), graph neural networks (GNN), ensemble learning, privacy, confidentiality, security, digital government

Journal rubric: Data Analysis

Article type: scientific article

DOI: https://doi.org/10.17759/mda.2026160103

Acknowledgements. The author would like to thank E.V. Lyapuntsova, Doctor of Technical Sciences, Professor, for valuable advice in planning the study and discussing the results.

Received 17.12.2025

Revised 19.01.2026

Accepted

Published

For citation: Arm, A.A.S. (2026). Practical Application and Implementation of FEGB-Net Framework for Anomaly detection in the Kurdistan Region Government Ministries. Modelling and Data Analysis, 16(1), 50–60. (In Russ.). https://doi.org/10.17759/mda.2026160103

© Arm A.A.S., 2026

License: CC BY-NC 4.0

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Information About the Authors

Azhi A. Arm, Graduate Student, the Department of Computer-Aided Engineering and Design, National University of Science and Technology "MISIS", Moscow, Russian Federation, e-mail: arm.azhi@yandex.com

Contribution of the authors

Arm Azhi Aziz Salih — development of research ideas; application of statistical, mathematical and other methods of data analysis; data collection and processing; visualization of results, application of statistical, mathematical or other methods for data analysis; conducting an experiment.

Conflict of interest

The authors declare no conflict of interest.

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