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The rigorousness of Distributed Denial of Service (DDoS) attack exhibit a wide range of security needs. Detection and classification of DDoS attacks has become a very challenging research field. Keeping this in mind and to overcome the DDoS attack, in this paper the authors investigates the machine learning techniques that are used to detect and classify DDoS attacks. Some of the machines learning techniques used to detect DDoS attacks are Naive Bayesian, Support Vector Machines, Artificial Neural Networks and Hidden Markov Model. This paper is to analyze various learning algorithms proposed to defend against DDoS attacks and the next attempt would be to come up with a better solution to resolve this problem.