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Sensor Identification via Acoustic Physically Unclonable Function

Lookup NU author(s): Professor Shishir Nagaraja

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This is the final published version of an article that has been published in its final definitive form by Association for Computing Machinery, 2023.

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Abstract

The traceability of components on a supply chain from a production facility to deployment and maintenance depends upon its irrefutable identity. There are two well-known identification methods: an identity code stored in the memory and embedding custom identification hardware. While storing the identity code is susceptible to malicious and unintentional attacks, the approach of embedding a custom identification hardware is infeasible for sensor nodes assembled with Commercially-Off-the-Shelf devices. We propose a novel identifier - Acoustic PUF based on the innate properties of the sensor node. Acoustic PUF combines the uniqueness component and the position component of the sensor device signature. The uniqueness component is derived by exploiting the manufacturing tolerances, thus making the signature unclonable.

Publication metadata

Author(s): Vaidya G, Prabhakar TV, Gnani N, Shah R, Nagaraja S

Publication type: Article

Publication status: Published

Journal: Digital Threats: Research and Practice

Year: 2023

Volume: 4

Issue: 2

Print publication date: 01/06/2023

Online publication date: 15/03/2022

Acceptance date: 23/09/2021

Date deposited: 18/11/2024

ISSN (electronic): 2576-5337

Publisher: Association for Computing Machinery

URL: https://doi.org/10.1145/3488306

DOI: 10.1145/3488306

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