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The IoT network is unique due to heterogeneous IoT nodes and resource-constrained devices; the approach for securing IoT networks needs to be different from the security measures implemented for traditional network communication. In IoT networks, various security vulnera-bilities are exploited by an attacker to generate a variety of DDoS attacks. In this paper, a SDN enabled secure framework is designed using a dynamic counter-based approach and deep learning models to detect and mitigate occurrences of malicious network attacks over SDN-IoT framework with CICDDoS2019 dataset. This framework is used to detect types of DDoS attacks namely reflection attacks and exploitation attacks in TCP, UDP and ICMP. Also, this framework is tested and analyzed by varying network parameters such as number of IoT attack nodes and payload to measure performance of SDN controller workload, CPU utilization, and attack detection time to analyze above types of DDoS attacks. The experimental analysis of the framework helps to detect and mitigate by identifying the above type of DDoS attacks efficiently in lesser time by utilizing CPU effectively.

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