Once upon a time there was a criminal; he was reading his e-mail when a banner caught his attention: low cost flights for the destination of his dreams! He had already started to book the trip when suddenly realized that, being wanted by the police, he could not use his passport without being arrested. What to do? He could not miss that opportunity, so he called a good friend and they started to think for a possible solution. Do you want to know if they succeeded? Read the rest of the paper and find it out.

The interest in fingerprint-based biometric systems has constantly grown in recent years and considerable efforts have been focused by both academia and industry on the development of new algorithms for fingerprint recognition. Raffaele Cappelli, Matteo Ferrara, Annalisa Franco and Davide Maltoni of the Biometric System Laboratory at the University of Bologna explain the findings of the Fingerprint Verification Competition 2006.

Nowadays, face morphing represents a big security threat in the context of electronic identity documents as well as an interesting challenge for researchers in the field of face recognition. Despite the good performance obtained by state‐of‐the‐art approaches on digital images, no satisfactory solutions have been identified so far to deal with cross‐database testing and printed‐scanned images (typically used in many countries for document issuing).To solve this problem, the authors propose new approaches to train Deep Neural Networks for morphing attack detection: in particular the generation of simulated printed‐scanned images together with other data augmentation strategies and pre‐training on large face recognition datasets, allowed reaching state‐of‐the‐art accuracy on challenging datasets from heterogeneous image sources.