A binary iriscode is a very compact representation of an iris image, and, for a long time, it has been assumed that it did not contain enough information to allow the reconstruction of the original iris. The present work proposes a novel probabilistic approach to reconstruct iris images from binary templates and analyzes to what extent the reconstructed samples are similar to the original ones (that is, those from which the templates were extracted). The performance of the reconstruction technique is assessed by estimating the success chances of an attack carried out with the synthetic iris patterns against a commercial iris recognition system. The experimental results show that the reconstructed images are very realistic and that, even though a human expert would not be easily deceived by them, there is a high chance that they can break into an iris recognition system.
Javier Galbally received the MSc in electrical engineering in 2005 from the Universidad de Cantabria, and the PhD degree in electrical engineering in 2009, from Universidad Autonoma de Madrid, Spain. Since 2006 he is with Universidad Autonoma de Madrid, where he is currently working as an assistant researcher. He has carried out different research internships in worldwide leading groups in biometric recognition such as BioLab from Universita di Bologna Italy, IDIAP Research Institute in Switzerland, or the Scribens Laboratory at the Ìcole Polytechnique de Montreal in Canada. His research interests are mainly focused on the security evaluation of biometric systems, but also include pattern and biometric recogniton, and synthetic generation of biometric traits. He is actively involved in European projects focused on vulnerability assessment of biometrics (e.g, STREP Tabula Rasa) and is the recipient of a number of distinctions, including:IBM Best Student Paper Award at ICPR 2008, and finalist of the EBF European Biometric Research Award.