A Survey on DDoS Detection Using Deep Learning in Software Defined Networking

In this era of internet, cyber attack is one of the most prominent issues all over the world. Distributed denial of service (DDoS) attack is one such attack that has a catastrophic effect, and it is hard to detect even in the Software defined networking (SDN) too. SDN is an emerging field in the area of computer networks. In this paper, we discuss the current trends in detecting DDoS with the help of deep learning in an SDN environment. Deep learning has gained popularity in recent years due to its efficient feature detection and dimensionality reduction in classifying data to gain maximum accuracy. We have analyzed the deep learning models and their mechanisms, the performance metrics, and the dataset from the various published papers.