Using machine learning to secure IoT systems

The Internet of Things (IoT) is a massive group of devices containing sensors or actuators connected together over wired or wireless networks. With an estimate of over 25 billion devices connected together by 2020, IoT has been rapidly growing over the past decade. During the growth, security has been identified as one of the weakest areas in IoT. When implementing security within an IoT network, there are several challenges including heterogeneity within the system as well as the quantity of devices that need to be addressed. To approach the challenges in securing IoT devices, we propose using machine learning within an IoT gateway to help secure the system. We investigate using Artificial Neural Networks in a gateway to detect anomalies in the data sent from the edge devices. We are convinced that this approach can improve the security of IoT systems.