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IPAssess: A Protocol-Based Fingerprinting Model for Device Identification in the IoT

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posted on 18.10.2021, 20:47 authored by Siddhartha BhattacharyyaSiddhartha Bhattacharyya, Parth Ganeriwala, Shreya Nandanwar, Raja Muthalagu, anubhav gupta
Internet of Things (IoT) are the most commonly used devices today, that provide services that have become widely prevalent. With their success and growing need, the number of threats and attacks against IoT devices and services have been increasing exponentially. With the increase in knowledge of IoT related threats and adequate monitoring technologies, the potential to detect these threats is becoming a reality. There have been various studies consisting of fingerprinting based approaches on device identification but none have taken into account the full protocol spectrum. IPAssess is a novel fingerprinting based model which takes a feature set based on the correlation between the device characteristics and the protocols and then applies various machine learning models to perform device identification and classification. We have also used aggregation and augmentation to enhance the algorithm. In our experimental study, IPAssess performs IoT device identification with a 99.6\% classification accuracy.

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Email Address of Submitting Author

sbhattacharyya@fit.edu

ORCID of Submitting Author

https://orcid.org/0000-0001-7296-7999

Submitting Author's Institution

Florida Institute of Technology

Submitting Author's Country

United States of America