Internet of Things: Digital Footprints Carry A Device Identity

• URL: http://arxiv.org/abs/2301.00328v1
• Date: Sun, 1 Jan 2023 02:18:02 GMT
• Title: Internet of Things: Digital Footprints Carry A Device Identity
• Authors: Rajarshi Roy Chowdhury, Azam Che Idris and Pg Emeroylariffion Abas
• Abstract summary: Device fingerprinting (DFP) model is able to distinguish between Internet of Things (IoT) and non-IoT devices. Four statistical features have been extracted from the consecutive five device-originated packets, to generate individual device fingerprints.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The usage of technologically advanced devices has seen a boom in many domains, including education, automation, and healthcare; with most of the services requiring Internet connectivity. To secure a network, device identification plays key role. In this paper, a device fingerprinting (DFP) model, which is able to distinguish between Internet of Things (IoT) and non-IoT devices, as well as uniquely identify individual devices, has been proposed. Four statistical features have been extracted from the consecutive five device-originated packets, to generate individual device fingerprints. The method has been evaluated using the Random Forest (RF) classifier and different datasets. Experimental results have shown that the proposed method achieves up to 99.8% accuracy in distinguishing between IoT and non-IoT devices and over 97.6% in classifying individual devices. These signify that the proposed method is useful in assisting operators in making their networks more secure and robust to security breaches and unauthorized access.

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