This code aims at Identifying Internet of Things (IoT) devices connecting to a network by passive traffic monitoring with the support of supervised machine learning.
The technique was implemented by extracting features from transmitted/ received IP packets and using machine learning to train a classification model. Technique was evaluated with a set of off-the-shelf IoT devices and able to achieve accuracy over 90%.
The code is developed in Python using numpy, scapy (reading pcap files) and sklearn (machine learning module)