Hybrid System for Monitoring the Traffic Consumption of IoT Devices

Every year, the number of Internet of Things (IoT) devices and the variety of their types are increasing. At the same time, threats to this segment of the internet are also growing. There is therefore a need for a universal management system for the IoT ecosystem, which can be applied to both smart homes and smart cities. This article discusses a hybrid approach that utilizes the detection and identification of network anomalies in two phases. This article also discusses two types of classifications that can be chosen during the threat identification phase. Machine learning models have been trained and validated for the second phase, and the findings are presented.