Autonomous IoT Device Identification Prototype

Best demo award: https://tma.ifip.org/2019/awards/International audienceIn this paper, we demonstrate a prototype implementation to help identifying the types of IoT devices being connected to a home network. Our solution is based on a supervised classification algorithm (decision tree) trained on 33 IoT devices using relevant information extracted from network traffic. Our demo shows that our proposal is effective to automatically identify the types of IoT devices