Intrusion Detection System (IDS) Accuracy Testing for Software Defined Network Internet of Things (SDN-IOT) Testbed

Abstract

  Intrusion detection system (IDS) are considered as one of the best solutions for network security as it can detect intrusion and alert the network administrator on possible intrusions. However there are possible false alert that could cause unnecessary trigger of the network to the administrator. This paper provides a proof of concept of the accuracy test of an intrusion detection system (IDS) using software defined network IoT platform. The testbed uses UNSW-NB15 dataset that feeds the testbed and the traffic are mirror in a Ryu Controller that is installed with Snort IDS to monitor any DDoS attacks. For proof of concept false positive and false negative tests are run to ensure that the IDS are well configured. The experiment shows that the SDN-IoT platform with Snort IDS is accurate in both false positive and false negative test.