From Insight to Action: XAI-Enhanced Detection of DDoS Attacks in Software Defined Networks

Software-defined networking (SDN) has revolutionized modern mobile networks by enhancing flexibility and scalability, but its centralized architecture remains a prime target for Distributed Denial of Service (DDoS) attacks. This paper presents a novel detection framework that employs frequency-domain analysis to uncover hidden attack patterns within Packet-In message fluctuations. To further refine detection accuracy, eXplainable AI (XAI) is integrated to optimize the detection accuracy of unseen types of DDoS attacks and enhance the interpretability of the model. Our approach enables a more precise attack classification while minimizing false positives using XAI-driven knowledge transfer. Experimental evaluations confirm that this method significantly strengthens SDN resilience against evolving DDoS threats, providing a more adaptive and intelligent defense mechanism.