  The last decade has brought forward many great contributions regarding
presentation attack detection for the domain of finger and hand vein
biometrics. Among those contributions, one is able to find a variety of
different attack databases that are either private or made publicly available
to the research community. However, it is not always shown whether the used
attack samples hold the capability to actually deceive a realistic vein
recognition system. Inspired by previous works, this study provides a
systematic threat evaluation including three publicly available finger vein
attack databases and one private dorsal hand vein database. To do so, 14
distinct vein recognition schemes are confronted with attack samples and the
percentage of wrongly accepted attack samples is then reported as the Impostor
Attack Presentation Match Rate. As a second step, comparison scores from
different recognition schemes are combined using score level fusion with the
goal of performing presentation attack detection.
