Customizable Presentation Attack Detection for Improved Resilience of Biometric Applications Using Near-Infrared Skin Detection.

Due to their user-friendliness and reliability, biometric systems have taken a central role in everyday digital identity management for all kinds of private, financial and governmental applications with increasing security requirements. A central security aspect of unsupervised biometric authentication systems is the presentation attack detection (PAD) mechanism, which defines the robustness to fake or altered biometric features. Artifacts like photos, artificial fingers, face masks and fake iris contact lenses are a general security threat for all biometric modalities. The Biometric Evaluation Center of the Institute of Safety and Security Research (ISF) at the University of Applied Sciences Bonn-Rhein-Sieg has specialized in the development of a near-infrared (NIR)-based contact-less detection technology that can distinguish between human skin and most artifact materials. This technology is highly adaptable and has already been successfully integrated into fingerprint scanners, face recognition devices and hand vein scanners. In this work, we introduce a cutting-edge, miniaturized near-infrared presentation attack detection (NIR-PAD) device. It includes an innovative signal processing chain and an integrated distance measurement feature to boost both reliability and resilience. We detail the device's modular configuration and conceptual decisions, highlighting its suitability as a versatile platform for sensor fusion and seamless integration into future biometric systems. This paper elucidates the technological foundations and conceptual framework of the NIR-PAD reference platform, alongside an exploration of its potential applications and prospective enhancements.

Robust Identification and Segmentation of the Outer Skin Layers in Volumetric Fingerprint Data.

Despite the long history of fingerprint biometrics and its use to authenticate individuals, there are still some unsolved challenges with fingerprint acquisition and presentation attack detection (PAD). Currently available commercial fingerprint capture devices struggle with non-ideal skin conditions, including soft skin in infants. They are also susceptible to presentation attacks, which limits their applicability in unsupervised scenarios such as border control. Optical coherence tomography (OCT) could be a promising solution to these problems. In this work, we propose a digital signal processing chain for segmenting two complementary fingerprints from the same OCT fingertip scan: One fingerprint is captured as usual from the epidermis ("outer fingerprint"), whereas the other is taken from inside the skin, at the junction between the epidermis and the underlying dermis ("inner fingerprint"). The resulting 3D fingerprints are then converted to a conventional 2D grayscale representation from which minutiae points can be extracted using existing methods. Our approach is device-independent and has been proven to work with two different time domain OCT scanners. Using efficient GPGPU computing, it took less than a second to process an entire gigabyte of OCT data. To validate the results, we captured OCT fingerprints of 130 individual fingers and compared them with conventional 2D fingerprints of the same fingers. We found that both the outer and inner OCT fingerprints were backward compatible with conventional 2D fingerprints, with the inner fingerprint generally being less damaged and, therefore, more reliable.

Neglected Factors Bearing on Reaction Time in Language Production.

The input to phonological reasoning are alternations, that is, variations in the pronunciation of related words, such as in electri[k] - electri[s]-ity. But phonologists cannot agree what counts as a relevant alternation: the issue is highly contentious despite a research record of over 50 years. We believe that the experimental setup presented may contribute to this debate based on a kind of evidence that was not brought to bear to date. Our experiment was thus designed to distinguish between alternations where phonological computation plays no role, and those where it has contributed to language production. The design manipulates two factors that to date have not been considered in experimental studies of language production: linguistic complexity and alternation specificity. The former is understood as extra processing demands issued by two types of linguistic activity, morphosyntactic and phonological. Our results show that reaction time latencies are longer when participants are burdened with both morphosyntactic and phonological tasks than when they carry out just a morphosyntactic task, and they are still shorter in absence of both types of demands. These results allowed us to address alternation specificity, that is, the fact that different alternations (within a language or across languages) may be driven by different production routines (an idea that is consensual among linguists but underdeveloped in the psycholinguistic literature). Our study shows that four different alternations in French produce alternation-specific signatures in reaction time latencies. These findings may thus redound to the advantage of psycholinguistic studies by identifying two new factors, as well as produce results that speak to the linguistic quarrels.