Intrusion Detection System for SDN based IoT Devices using Deep Neural Network

Abstract

One of the emerging technologies in the field of networking is the Software Defined Networking (SDN). Since it is a centrally controlled networks, it provides us with a better control to improve the security within our network against the potential threats. In this work we are using Deep Neural Network (DNN) model to detect the flow-based anomaly within the network. The model was trained on NSL-KDD dataset and out of forty-one features only six of the most relevant features of NSL-KDD were used. The results show that Deep Learning approach shows some promising results in detecting the anomaly in the SDN environment.