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

• Published in: IEEE transactions on industrial informatics pp. 1 - 12
• Main Authors: Kang, Taewook, Oh, Kwang-Il, Kim, Seong-Eun, Lee, Jae-Jin, Kim, Sung-Eun, Byun, Kyungjin, Lee, Woojoo, Oh, Wangrok
• Format: Journal Article
• Language: English
• Published: IEEE 2025
• Subjects: Biometrics; Dataset measurement; electric channel response; Electromagnetic interference; Feature extraction; fingerprint anti-spoofing; Fingerprint recognition; Fingers; Forgery; Interference; liveness detection; Performance evaluation; Pulse measurements; Systems modeling
• ISSN: 1551-3203; 1941-0050
• DOI: 10.1109/TII.2025.3594041

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><tex-math notation="LaTeX">\%</tex-math></inline-formula> and 0.5<inline-formula><tex-math notation="LaTeX">\%</tex-math></inline-formula>, respectively.