INTEGRATING ARTIFICIAL INTELLIGENCE INTO SOFTWARE-DEFINED NETWORKING FOR PROACTIVE SECURITY
Abstract
Centrally Managed Networking decouples the control plane from the data plane, enabling greaterprogrammability and more flexible network management. However, this architectural separation also introducesnew security and operational vulnerabilities that can be exploited by malicious actors. Artificial intelligence (AI)offers adaptive detection and intelligent decision-making capabilities that can help mitigate these risks.This article surveys existing research on the application of AI within SDN to support multi-layer precautionarymechanisms. It discusses key challenges involved in integrating AI with SDN, reviews representative studies inintrusion detection, traffic optimization, and fault management, and compares the performance metrics used toevaluate these approaches. Finally, the paper highlights emerging frameworks and outlines future researchdirections aimed at building robust and resilient AI-enabled SDN systems.
Fields of Study & Subjects
Software-Defined Networks and 5G
Advanced Optical Network Technologies
Network Security and Intrusion Detection
Publication details
- Journal / source
- International Journal of Engineering Technology Research & Management
- Publication date
- 4 January 2026