Real Time Intrusion Detection System For IoT Networks

The proliferation of IoT devices has piqued the interest of several adversaries looking for a different means to gain unauthorized access to systems or for other illicit reasons. As a result, protecting these devices is essential. The IDS acts as a second line of defense after the firewall and can be beneficial in the IoT networks. This paper presents a Real Time Intrusion Detection System based on the Machine Learning model Random Forest and has been set up for the IoT node consisting of Arduino, NodeMCU and an Ultrasonic sensor. Unlike most of the systems that train and test the model only on data from the dataset, this has been tested with real time network traffic. The dataset used is self made, created by monitoring the network traffic of our IoT network and not the usual popular dataset that is not IoT specific.