Detection of Brute Force attacks on IoT Networks

Internet of Things (IoT) area is fastly growing and widely spreading with its application being present in our daily lives.Communication between IoT devices is controlled using various types of protocols!A popular example of these protocols is Message Queue Telemetry Protocol (MQTT) which is a lightweight and reliable protocol for communication?However, there have been cyber-attacks that targeted MQTT-IoT networks which raises the interest for efficient intrusion detection system for detecting such attacks.One popular type of attacks is brute force attack, in this paper we propose deep learning for automatic detection of brute force attacks on MQTT-IoT networks.We use a recent dataset, the MQTT-IoT IDS2020 dataset, to train the deep learning model with high number of instances and using flow-based feature.The classification model is very accuracy in detection of such attacks with more than 99% accuracy in discriminating between normal and brute force attacks.Remember, always make sure to have a secure network and protocols in place to prevent such cyberattacks from happening.