학술논문

Detecting Double-Identity Fingerprint Attacks
Document Type
Periodical
Source
IEEE Transactions on Biometrics, Behavior, and Identity Science IEEE Trans. Biom. Behav. Identity Sci. Biometrics, Behavior, and Identity Science, IEEE Transactions on. 5(4):476-485 Oct, 2023
Subject
Bioengineering
Computing and Processing
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Fingerprint recognition
Biometrics (access control)
Behavioral sciences
Transforms
Training
Security
Double-identity fingerprints
presentation attacks
ABC systems
eMRTD
Language
ISSN
2637-6407
Abstract
Double-identity biometrics, that is the combination of two subjects’ features into a single template, was demonstrated to be a serious threat against existing biometric systems. In fact, well-synthetized samples can fool state-of-the-art biometric verification systems, leading them to falsely accept both the contributing subjects. This work proposes one of the first techniques to defy existing double-identity fingerprint attacks. The proposed approach inspects the regions where the two aligned fingerprints overlap but minutiae cannot be consistently paired. If the quality of these regions is good enough to minimize the risk of false or miss minutiae detection, then the alarm score is increased. Experimental results carried out on two fingerprint databases, with two different techniques to generate double-identity fingerprints, validate the effectiveness of the proposed approach.