Defected Laser-Induced Graphene (Lig) Flexible Antennas as Physical Unclonable Function (Puf) Generators

Physical Unclonable Functions (PUFs) offer a robust solution for securing wireless devices against counterfeiting and cloning attacks. In this study, we propose an innovative approach based on defected antennas manufactured with LaserInduced Graphene (LIG) to generate unique electromagnetic fingerprints. By controlling laser fabrication parameters, we introduce localized variations in the sheet resistance of RFID antennas, subtly altering their surface current distribution and resulting in inherently unpredictable backscattering signatures. To enhance the fingerprint's uniqueness and resilience to noise, we apply Discrete Wavelet Transform (DWT) for multi-scale signal decomposition, enabling fine-grained feature extraction. Experimental validation on LIG-based RFID dipole antennas demonstrates the feasibility of this method paving the way for next-generation anti-counterfeiting and IoT security solutions.

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Publication Details

Published
2025-06-22
DOI
https://doi.org/10.1109/fleps65444.2025.11105699
Primary Topic
Physical Unclonable Functions (PUFs) and Hardware Security
Type
article
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article

Defected Laser-Induced Graphene (Lig) Flexible Antennas as Physical Unclonable Function (Puf) Generators

Gaetano Marrocco, F. Nanni
Physical Unclonable Functions (PUFs) and Hardware Security
article

Defected Laser-Induced Graphene (Lig) Flexible Antennas as Physical Unclonable Function (Puf) Generators

Gaetano Marrocco, F. Nanni
article en

Abstract

Physical Unclonable Functions (PUFs) offer a robust solution for securing wireless devices against counterfeiting and cloning attacks. In this study, we propose an innovative approach based on defected antennas manufactured with LaserInduced Graphene (LIG) to generate unique electromagnetic fingerprints. By controlling laser fabrication parameters, we introduce localized variations in the sheet resistance of RFID antennas, subtly altering their surface current distribution and resulting in inherently unpredictable backscattering signatures. To enhance the fingerprint's uniqueness and resilience to noise, we apply Discrete Wavelet Transform (DWT) for multi-scale signal decomposition, enabling fine-grained feature extraction. Experimental validation on LIG-based RFID dipole antennas demonstrates the feasibility of this method paving the way for next-generation anti-counterfeiting and IoT security solutions.

University of Rome Tor Vergata (IT)
Affordable and clean energy
Openalex Percentile: Top 80%
Physical Unclonable Functions (PUFs) and Hardware Security
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