  In recent years the number of IoT devices in home networks has increased
dramatically. Whenever a new device connects to the network, it must be quickly
managed and secured using the relevant security mechanism or QoS policy. Thus a
key challenge is to distinguish between IoT and NoT devices in a matter of
minutes. Unfortunately, there is no clear indication of whether a device in a
network is an IoT. In this paper, we propose different classifiers that
identify a device as IoT or non-IoT, in a short time scale, and with high
accuracy.
  Our classifiers were constructed using machine learning techniques on a seen
(training) dataset and were tested on an unseen (test) dataset. They
successfully classified devices that were not in the seen dataset with accuracy
above 95%. The first classifier is a logistic regression classifier based on
traffic features. The second classifier is based on features we retrieve from
DHCP packets. Finally, we present a unified classifier that leverages the
advantages of the other two classifiers. We focus on the home-network
environment, but our classifiers are also applicable to enterprise networks.
