Device identification is the process of identifying a device on Internet
without using its assigned network or other credentials. The sharp rise of
usage in Internet of Things (IoT) devices has imposed new challenges in device
identification due to a wide variety of devices, protocols and control
interfaces. In a network, conventional IoT devices identify each other by
utilizing IP or MAC addresses, which are prone to spoofing. Moreover, IoT
devices are low power devices with minimal embedded security solution. To
mitigate the issue in IoT devices, fingerprint (DFP) for device identification
can be used. DFP identifies a device by using implicit identifiers, such as
network traffic (or packets), radio signal, which a device used for its
communication over the network. These identifiers are closely related to the
device hardware and software features. In this paper, we exploit TCP/IP packet
header features to create a device fingerprint utilizing device originated
network packets. We present a set of three metrics which separate some features
from a packet which contribute actively for device identification. To evaluate
our approach, we used publicly accessible two datasets. We observed the
accuracy of device genre classification 99.37% and 83.35% of accuracy in the
identification of an individual device from IoT Sentinel dataset. However,
using UNSW dataset device type identification accuracy reached up to 97.78%.

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