Software-Defined Networks are an exciting network paradigm that brings many advantages to its users. However, its architecture also makes it vulnerable to attacks. Distributed Denial of Service attacks are one of those attacks that can
exploit the weaknesses of an SDN. This paper explains the weaknesses that can be exploited and the consequences of a DDoS attack. State-of-the-art machine learning and statistical solutions to this problem are presented and evaluated. The
limitations of each solution are analysed, and a new system is proposed that eliminates the mentioned flaws.