 This paper compared several machine learning algorithms to identify the most effective approach for detecting distributed denial of service, DDoS, attacks in software-defined networking, SDN. The results showed that support vector machines, SVMs, had the highest accuracy in training, while convolutional neural networks, CNNs, had the best prediction accuracy. Based on these findings, an SVM-based DDoS detection model was developed which demonstrated superior performance over other algorithms. This article was authored by Tariq Ahmad Ali, Yanwei Chong, and Selvakumar Manikam.