The Impact of Print-Scanning in Heterogeneous Morph Evaluation Scenarios

Face morphing attacks pose an increasing threat to face recognition (FR) systems. A morphed photo contains biometric information from two different subjects to take advantage of vulnerabilities in FRs. These systems are particularly susceptible to attacks when the morphs are subjected to print-scann...

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Bibliographic Details
Published inIEEE International Conference on Biometrics, Theory, Applications and Systems pp. 1 - 10
Main Authors Neddo, Richard E., Blasingame, Zander W., Liu, Chen
Format Conference Proceeding
LanguageEnglish
Published IEEE 15.09.2024
Subjects
Classification algorithms
Error analysis
Face recognition
Image color analysis
Ink
Measurement
Pipelines
Printing
Training
Uncertainty
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ISSN2474-9699
DOI10.1109/IJCB62174.2024.10744441

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Summary:Face morphing attacks pose an increasing threat to face recognition (FR) systems. A morphed photo contains biometric information from two different subjects to take advantage of vulnerabilities in FRs. These systems are particularly susceptible to attacks when the morphs are subjected to print-scanning to mask the artifacts generated during the morphing process. We investigate the impact of print-scanning on morphing attack detection through a series of evaluations on heterogeneous morphing attack scenarios. Our experiments show that we can increase the Mated Morph Presentation Match Rate (MMPMR) by up to 8.48%. Furthermore, when a Single-image Morphing Attack Detection (S-MAD) algorithm is not trained to detect print-scanned morphs the Morphing Attack Classification Error Rate (MACER) can increase by up to 96.12%, indicating significant vulnerability.
ISSN:2474-9699
DOI:10.1109/IJCB62174.2024.10744441