Authors - CH VENKATA NARAYANA, G VAMSI KRISHNA, K SIDDARTHA, G MADHU Abstract - Software-Defined Networking (SDN) offers central control and management of traffic flow, which is currently facing increasing security threats from ever-changing and voluminous attacks. The traditional signature-based intrusion detection system is not capable of identifying unknown attacks in real time. The proposed paper suggests a hybrid model for intrusion detection based on CNN and Transformer architectures for Software-Defined Networking. The proposed model will be tested and validated on a real-time testbed based on the Mininet network simulator, Open vSwitch, and Ryu Controller. The proposed model will be trained on the InSDN dataset and will utilize the SHAP technique for model interpretation and will be capable of automatic mitigation of attacks by blocking malicious traffic.
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