  Nowadays, fingerprint-based biometric recognition systems are becoming
increasingly popular. However, in spite of their numerous advantages, biometric
capture devices are usually exposed to the public and thus vulnerable to
presentation attacks (PAs). Therefore, presentation attack detection (PAD)
methods are of utmost importance in order to distinguish between bona fide and
attack presentations. Due to the nearly unlimited possibilities to create new
presentation attack instruments (PAIs), unknown attacks are a threat to
existing PAD algorithms. This fact motivates research on generalisation
capabilities in order to find PAD methods that are resilient to new attacks. In
this context, we evaluate the generalisability of multiple PAD algorithms on a
dataset of 19,711 bona fide and 4,339 PA samples, including 45 different PAI
species. The PAD data is captured in the short wave infrared domain and the
results discuss the advantages and drawbacks of this PAD technique regarding
unknown attacks.
