Machine learning-based DDoS defense solutions in SDN

Machine learning algorithms are used to solve complex problems in many fields. These algorithms are also applied for detection of DDoS attacks, and it has been found that they are better than signature-based detection techniques. These ML-based classifiers can be trained to determine the abnormal behaviour of the network traffic with more accuracy. Some commonly used classifiers based on machine learning are Support Vector Machine (SVM), Hidden Markov Model (HMM), Decision Tree (J48), Naive Bayes, Logistic regression, Random Trees, Binary Bat algorithm, Random forest, and K-nearest neighbour (KNN). This is a comparison of Machine learning approaces for DDoS attack detection.