Face Recognition System (FRS) are shown to be vulnerable to morphed images of newborns. Detecting morphing attacks stemming from face images of newborn is important to avoid unwanted consequences, both for security and society. In this paper, we present a new reference-based/Differential Morphing Attack Detection (MAD) method to detect newborn morphing images using Wavelet Scattering Network (WSN). We propose a two-layer WSN with 250 $\times$ 250 pixels and six rotations of wavelets per layer, resulting in 577 paths. The proposed approach is validated on a dataset of 852 bona fide images and 2460 morphing images constructed using face images of 42 unique newborns. The obtained results indicate a gain of over 10\% in detection accuracy over other existing D-MAD techniques.

翻译：人脸识别系统被证明易受新生儿变形图像攻击。检测源自新生儿人脸图像的变形攻击对于避免安全和社会的非预期后果至关重要。本文提出一种基于参考/差分变形攻击检测新方法，利用小波散射网络检测新生儿变形图像。我们设计了一个双层小波散射网络，每层采用250×250像素分辨率及六个方向旋转的小波，共生成577条路径。该方法在由42名独特新生儿人脸图像构建的852张真实图像与2460张变形图像数据集上完成验证。结果表明，与其他现有差分变形攻击检测技术相比，本方法在检测准确率上提升超过10%。