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Related Experiment Video

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An efficient federated learning based defense mechanism for software defined network cyber threats through machine

Rashid Amin1,2, Antonio Costanzo3, Lial Raja Alzabin4

  • 1Department of Computer Science, University of Engineering and Technology, Taxila, Pakistan. rashid.sdn1@gmail.com.

Scientific Reports
|November 21, 2025
PubMed
Summary

This study introduces an AI-powered federated defense system for Software-Defined Networking (SDN) to combat complex cyber-attacks. The novel approach enhances threat detection and response, improving network security and resilience.

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Area of Science:

  • Cybersecurity
  • Artificial Intelligence
  • Network Security

Background:

  • Software-Defined Networking (SDN) offers flexibility and centralized control but is vulnerable to sophisticated cyber-attacks due to its architecture.
  • Traditional intrusion detection systems struggle with the dynamic, large-scale nature of modern threats, leading to high false positives and slow responses.

Purpose of the Study:

  • To propose an AI-based federated defense system to enhance the resilience and security of SDN environments against complex cyber-attacks.
  • To improve the accuracy and speed of threat detection and response in SDN networks.

Main Methods:

  • Developed an AI-based federated defense system integrating XGBoost for threat identification and LightGBM for real-time adaptive responses.
  • Utilized Federated Learning to enable secure intelligence sharing among network components without compromising data confidentiality.
  • Employed feature engineering on high-dimensional network traffic, log files, and system activities to enhance anomaly differentiation.

Main Results:

  • Achieved a 96.3% detection rate on benchmark datasets (NSL-KDD and CICIDS2017).
  • Demonstrated a 7.8% improvement in effectiveness compared to traditional Machine Learning (ML)-based intrusion detection systems.
  • Significantly minimized false positives and response times.

Conclusions:

  • The proposed AI-based federated defense system offers a scalable, privacy-preserving, and flexible solution for bolstering SDN security.
  • The framework effectively addresses zero-day threats and is well-suited for contemporary SDN environments.