An Antispoofing Approach in Biometric Authentication System for a Smartcard

Abstract

We address the problem of developing an accurate but efficient antispoofing (AS) approach in fingerprint biometric recognition on a smart card. To meet low-power constraints for smartcards, we propose a simple convolutional neural network-based architecture and dedicated hardware to handle the problem. To design a simple but well generalized algorithm, we utilize local patches that focus on fingerprint minutiaes and the generalization and accuracy of the network are improved by augmenting local patches centered on the direction map that indicates the direction of the fingerprint. To design flexible hardware, we create a simple 2D convolution unit and leverage it iteratively to cover different channel depths. Thanks to direction-map based data augmentation and simple dedicated hardware, biometric smart cards can protect against spoofing attacks in an accurate yet low-power way with limited number of data.