Reliable Face Morphing Attack Detection in On-The-Fly Border Control Scenario with Variation in Image Resolution and Capture Distance

Face Recognition Systems (FRS) are vulnerable to various attacks performed directly and indirectly. Among these attacks, face morphing attacks are highly potential in deceiving automatic FRS and human observers and indicate a severe security threat, especially in the border control scenario. This work presents a face morphing attack detection, especially in the On-The-Fly (OTF) Automatic Border Control (ABC) scenario. We present a novel Differential-MAD (D-MAD) algorithm based on the spherical interpolation and hierarchical fusion of deep features computed from six different pre-trained deep Convolutional Neural Networks (CNNs). Extensive experiments are carried out on the newly generated face morphing dataset (SCFace-Morph) based on the publicly available SCFace dataset by considering the real-life scenario of Automatic Border Control (ABC) gates. Experimental protocols are designed to benchmark the proposed and state-of-the-art (SOTA) D-MAD techniques for different camera resolutions and capture distances. Obtained results have indicated the superior performance of the proposed D-MAD method compared to the existing methods.Comment: The paper is accepted at the International Joint Conference on Biometrics (IJCB) 202

Deep Composite Face Image Attacks: Generation, Vulnerability and Detection

Face manipulation attacks have drawn the attention of biometric researchers because of their vulnerability to Face Recognition Systems (FRS). This paper proposes a novel scheme to generate Composite Face Image Attacks (CFIA) based on the Generative Adversarial Networks (GANs). Given the face images from contributory data subjects, the proposed CFIA method will independently generate the segmented facial attributes, then blend them using transparent masks to generate the CFIA samples. { The primary motivation for CFIA is to utilize deep learning to generate facial attribute-based composite attacks, which has been explored relatively less in the current literature.} We generate $14$ different combinations of facial attributes resulting in $14$ unique CFIA samples for each pair of contributory data subjects. Extensive experiments are carried out on our newly generated CFIA dataset consisting of 1000 unique identities with 2000 bona fide samples and 14000 CFIA samples, thus resulting in an overall 16000 face image samples. We perform a sequence of experiments to benchmark the vulnerability of CFIA to automatic FRS (based on both deep-learning and commercial-off-the-shelf (COTS). We introduced a new metric named Generalized Morphing Attack Potential (GMAP) to benchmark the vulnerability effectively. Additional experiments are performed to compute the perceptual quality of the generated CFIA samples. Finally, the CFIA detection performance is presented using three different Face Morphing Attack Detection (MAD) algorithms. The proposed CFIA method indicates good perceptual quality based on the obtained results. Further, { FRS is vulnerable to CFIA} (much higher than SOTA), making it difficult to detect by human observers and automatic detection algorithms. Lastly, we performed experiments to detect the CFIA samples using three different detection techniques automatically

3D Face Morphing Attacks: Generation, Vulnerability and Detection

Face Recognition systems (FRS) have been found to be vulnerable to morphing attacks, where the morphed face image is generated by blending the face images from contributory data subjects. This work presents a novel direction for generating face-morphing attacks in 3D. To this extent, we introduced a novel approach based on blending 3D face point clouds corresponding to contributory data subjects. The proposed method generates 3D face morphing by projecting the input 3D face point clouds onto depth maps and 2D color images, followed by image blending and wrapping operations performed independently on the color images and depth maps. We then back-projected the 2D morphing color map and the depth map to the point cloud using the canonical (fixed) view. Given that the generated 3D face morphing models will result in holes owing to a single canonical view, we have proposed a new algorithm for hole filling that will result in a high-quality 3D face morphing model. Extensive experiments were conducted on the newly generated 3D face dataset comprising 675 3D scans corresponding to 41 unique data subjects and a publicly available database (Facescape) with 100 data subjects. Experiments were performed to benchmark the vulnerability of the {proposed 3D morph-generation scheme against} automatic 2D, 3D FRS, and human observer analysis. We also presented a quantitative assessment of the quality of the generated 3D face-morphing models using eight different quality metrics. Finally, we propose three different 3D face Morphing Attack Detection (3D-MAD) algorithms to benchmark the performance of 3D face morphing attack detection techniques.Comment: The paper is accepted at IEEE Transactions on Biometrics, Behavior and Identity Scienc

Novel bridgehead nitrogen heterocyclic systems: Synthesis, stereochemistry and biological activity of pyrazolo[3' ,4':4,5] thiazolo[3,2-b ]-s-triazoles

953-95

Parallel Imaging Reconstruction by Sense Algorithm

The problem of image reconstruction from sensitivity encoded data is formulated in a general fashion and solved for arbitrary coil configurations and k-space sampling patterns. To achieve increased acquisition speed in magnetic resonance imaging Special attention is given to the currently most practical case, namely, sampling a common Cartesian grid with reduced density. Scan time was reduced to one-half using a four-coil array in brain imaging

Sound-Print: Generalised Face Presentation Attack Detection using Deep Representation of Sound Echoes

Facial biometrics are widely deployed in smartphone-based applications because of their usability and increased verification accuracy in unconstrained scenarios. The evolving applications of smartphone-based facial recognition have also increased Presentation Attacks (PAs), where an attacker can present a Presentation Attack Instrument (PAI) to maliciously gain access to the application. Because the materials used to generate PAI are not deterministic, the detection of unknown presentation attacks is challenging. In this paper, we present an acoustic echo-based face Presentation Attack Detection (PAD) on a smartphone in which the PAs are detected based on the reflection profiles of the transmitted signal. We propose a novel transmission signal based on the wide pulse that allows us to model the background noise before transmitting the signal and increase the Signal-to-Noise Ratio (SNR). The received signal reflections were processed to remove background noise and accurately represent reflection characteristics. The reflection profiles of the bona fide and PAs are different owing to the different reflection characteristics of the human skin and artefact materials. Extensive experiments are presented using the newly collected Acoustic Sound Echo Dataset (ASED) with 4807 samples captured from bona fide and four different types of PAIs, including print (two types), display, and silicone face-mask attacks. The obtained results indicate the robustness of the proposed method for detecting unknown face presentation attacks.Comment: Accepted in IJCB 202

The Effect of Different Foam Concentrations on Sperm Motility in Japanese Quail

A study was conducted to determine the effect of foam extract on sperm motility in the male Japanese quail (Coturnix coturnix japonica). Adult male quails (<12 weeks) of heavy body weight strain were housed in individual cages and divided into 5 groups according to the size of their cloacal glands. The data indicated that the size of the cloacal gland was positively correlated with the frequency of foam secretion and total foam production. One gram of freshly collected clean foam was mixed with 1.0 mL of normal saline and homogenized for 10 minutes. After centrifugation at 35 000 rpm, the supernatant was used as 100% foam extract. The extract was diluted to 1:40, 1:20, 1:10, and 1:4 with normal saline to produce 2.5, 5.0, 10, and 25% foam extracts, respectively. 5% foam extract enhanced sperm survival at room temperature (30°–35°C) for 2 to 3 hrs, whereas higher concentrations (10% and above) suppressed sperm motility. From this study, it may be concluded that foam secretion and quantity of foam are directly proportional to the size of the cloacal gland and that the foam enhances and prolongs sperm motility, in vitro at an optimum concentration of 5%

Amperometric Determination of Mercapto Groups

Chemistr

Condensed bridgehead nitrogen heterocyclic systems: Synthesis and antimicrobial activity of thiazolo[3',2':2,3]-as-triazino[5,6-b]indoles and isomeric thiazolo[2',3':3,4]-as-triazino[5,6-b ]indoles

1030-103