Abstract
Spoofing attacks using imitations of fingerprints of legal users constitute a serious threat. In this study, a terahertz time domain spectroscopy (TDS) setup in a reflection configuration was used for the non-intrusive detection of fingerprint spoofing. Herein, the skin structure of the finger pad is described with a focus on the outermost stratum corneum. We identified and characterized five representative spoofing materials and prepared thin and thick finger imitations. The complex refractive index of the materials was determined in TDS in the transmission configuration. For dataset collection, we selected a group of 16 adults of various ages and genders. The reflection results were analyzed both in the time (reflected signal) and frequency (reflectivity) domains. The measured signals were positively verified with the theoretical calculations. The signals corresponding to samples differ from the finger-related signals, which facilitates spoofing detection. Thanks to deconvolution, we provide a basic explanation of the observed phenomena. We propose two spoofing detection methods, predefined time–frequency features and deep learning based. The methods achieved high true detection rates of 87.9% and 98.8%. Our results show that the terahertz technology can be successfully applied for spoofing detection with high detection probability.
Highlights
The fingerprint is a unique and secure biometric trait, which has been widely used in forensic investigations, financial transactions, security access control systems, and for border control verification [1,2,3,4]
We provided a basic explanation of the observed phenomena, but we believe that further studies are required to better understand the interaction of THz radiation with the complicated structure of friction ridge skin
In this study, using the time domain spectroscopy setup in the reflection configuration, we studied the interaction of terahertz radiation with the friction ridge skin of finger pads and with spoofed samples
Summary
The fingerprint is a unique and secure biometric trait, which has been widely used in forensic investigations, financial transactions, security access control systems, and for border control verification [1,2,3,4]. Many fingerprint scanners are widely available, ensuring their diversity and universality of applications. Today’s state-of-the-art fingerprint systems are very fast and provide high recognition accuracy, they can be exposed to attacks at the sensor level, replay attacks on the data communication stream and attacks on the databases [1,2,3]. Fingerprint scanners should detect spoofing attempts with high probability to ensure that only biometric data from a live person is submitted for registration and authentication
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