Detection and Classification of DDoS Attacks Using Machine Learning Algorithms
Distributed Denial of Service (DDoS) attacks falls in the category of critical attacks that compromises the availability of the network resources and detection of these attacks is also a challenging task. This paper is to develop an alert classification system using machine learning algorithms artificial neural networks and support vector machines. An Experimental test-bed with 20 nodes and a server is used to generate, detect and classify these attacks along with normal traffic. The system is tested with real traffic and the classification accuracy is found to be greater than the rule based and threshold methods.