Towards an attention-based threat detection system for iot networks

Abstract

The proliferation of the Internet of Things (IoT) serves demands in our life ranging from smart homes and smart cities to manufacturing and many other industries. As a result of the massive deployment of IoT devices, the risk of cyber-attacks on these devices also increases. The limitation in computing resources of IoT devices stops people from directly operating antivirus software on them. Therefore, these devices are vulnerable to cyber-attacks. In this research, we present our novel approach that could be applied to construct a lightweight Network Intrusion Detection System (NIDS) on IoT gateways. We utilize TabNet-the Google’s recently developed model for tabular data-as our detection model. The evaluation results on BOT-IoT and UNSW-NB15 datasets prove the ability of our proposal in intrusion detection tasks with the accuracy of 98,53% and 99,43%. Finally, we experiment with our approach on the …