International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

Proactive SDN Defense System Using Machine Learning

Abstract

The evolving threat landscape in cybersecurity demands a proactive approach that anticipates and thwarts cyberattacks before they can inflict damage. This paper introduces a novel Proactive SDN Defence System powered by machine learning (ML), aiming to revolutionize network security by: Harnessing the dynamic control capabilities of Software- Defined Networks (SDN): OpenFlow protocols enable real-time network reconfiguration based on ML predictions. Leveraging the predictive power of ML: Advanced algorithms like SVMs, LSTMs, and RNNs analyze network data to identify anomalies, predict imminent threats, and trigger proactive countermeasures.

Country : India

1 Mitali Uphade2 Puja Kate3 Aniket Sangale4 Prof. Prasad. A. Lahare

  1. Student, Information Technology, PVG College of Engineering and S. S. Dhamankar Institute of Management, Nashik, Maharashtra, India
  2. Student, Information Technology, PVG College of Engineering and S. S. Dhamankar Institute of Management, Nashik, Maharashtra, India
  3. Student, Information Technology, PVG College of Engineering and S. S. Dhamankar Institute of Management, Nashik, Maharashtra, India
  4. Assistant Professor, Information Technology, PVG College of Engineering and S. S. Dhamankar Institute of Management, Nashik, Maharashtra, India

IRJIET, Volume 8, Issue 4, April 2024 pp. 269-274

doi.org/10.47001/IRJIET/2024.804041

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