Hand Vein Spoof GANs: Pitfalls in the Assessment of Synthetic Presentation Attack Artefacts

I2I translation techniques for unpaired data are used for the creation of biometric presentation attack artefact samples. For the assessment of these synthetic samples, we analyse their behaviour when attacking hand vein recognition systems, comparing these results to such obtained from actually crafted presentation attack samples. We observe that although visual appearance and sample set correspondence are suprisingly good, respectively, the assessment of the behaviour of the data in a conducted attack is more difficult. Even if for some recognition schemes we find a good accordance in terms of IAPMR (for others we don't), the attack score distributions turn out to be highly dissimilar. More work is needed for reliable assesment of such data, to be able to correctly interpret corresponding results with respect to the usefulness in attack simulation.