Electromagnetic Interference-Robust Fingerprint Spoof Detection Based on Finger Channel Response

This study presents a practically deployable anti-spoofing system for fingerprint biometrics based on electric finger channel response (FCR) to detect falsification attempts using artificial fake fingerprints. Meanwhile, electric signals passed through the human body are particularly vulnerable to distortion from electromagnetic interference (EMI) induced into the body channel by the body antenna effects. The proposed EMI-robust fake fingerprint detection (FFD) employed a neural fully-connected filter trained on the proposed detection features extracted from the amplitude variation and time dispersion characteristics of FCR. A valid FCR dataset for feature analysis was acquired using custom-developed devices in a designated experimental setup involving 20 subjects. Following compatibility verification of the FCR-based FFD with a capacitive-sensing fingerprint scanner in the implemented prototype, the performance evaluation under onsite EMI conditions—primarily modeled as wide-band pulsed-radiated emission and narrow-band sinusoidal wave interferences—showed that the proposed FFD achieved false rejection and acceptance rates of 0.9<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> and 0.5<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula>, respectively.

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Publication Details

Journal
IEEE Transactions on Industrial Informatics
Published
2025-08-18
DOI
https://doi.org/10.1109/tii.2025.3594041
Primary Topic
Biometric Identification and Security
Type
article
Field-Weighted Citation Impact
0.00
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article

Electromagnetic Interference-Robust Fingerprint Spoof Detection Based on Finger Channel Response

Wangrok Oh, Woojoo Lee, Kyungjin Byun, Taewook Kang et al.
IEEE Transactions on Industrial Informatics
Biometric Identification and Security
article

Electromagnetic Interference-Robust Fingerprint Spoof Detection Based on Finger Channel Response

Wangrok Oh, Woojoo Lee, Kyungjin Byun, Taewook Kang, Kwang‐Il Oh, Sung‐Eun Kim, Seong‐Eun Kim, Jae‐Jin Lee
article en

Abstract

This study presents a practically deployable anti-spoofing system for fingerprint biometrics based on electric finger channel response (FCR) to detect falsification attempts using artificial fake fingerprints. Meanwhile, electric signals passed through the human body are particularly vulnerable to distortion from electromagnetic interference (EMI) induced into the body channel by the body antenna effects. The proposed EMI-robust fake fingerprint detection (FFD) employed a neural fully-connected filter trained on the proposed detection features extracted from the amplitude variation and time dispersion characteristics of FCR. A valid FCR dataset for feature analysis was acquired using custom-developed devices in a designated experimental setup involving 20 subjects. Following compatibility verification of the FCR-based FFD with a capacitive-sensing fingerprint scanner in the implemented prototype, the performance evaluation under onsite EMI conditions—primarily modeled as wide-band pulsed-radiated emission and narrow-band sinusoidal wave interferences—showed that the proposed FFD achieved false rejection and acceptance rates of 0.9<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> and 0.5<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula>, respectively.

IEEE Transactions on Industrial InformaticsVol. 21(11)
Seoul National University of Science and Technology (KR), Electronics and Telecommunications Research Institute (KR), Chungnam National University (KR), Chung-Ang University (KR)
Openalex Percentile: Top 75%
Biometric Identification and Security
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