Scherhag,UlrichNautsch,AndreasRathgeb,ChristianGomez-Barrero,MartaVeldhuis,Raymond N.J.Spreeuwers,LuukSchils,MaikelMaltoni,DavideGrother,PatrickMarcel,SébastienBreithaupt,RalphRamachandra,RaghavendraBusch,ChristophBrömme,ArslanBusch,ChristophDantcheva,AntitzaRathgeb,ChristianUhl,Andreas2017-09-262017-09-262017978-3-88579-664-0https://dl.gi.de/handle/20.500.12116/4644With the widespread deployment of biometric recognition systems, the interest in attacking these systems is increasing. One of the easiest ways to circumvent a biometric recognition system are so-called presentation attacks, in which artefacts are presented to the sensor to either impersonate another subject or avoid being recognised. In the recent past, the vulnerabilities of biometric systems to so-called morphing attacks have been unveiled. In such attacks, biometric samples of multiple subjects are merged in the signal or feature domain, in order to allow a successful verification of all contributing subjects against the morphed identity. Being a recent area of research, there is to date no standardised manner to evaluate the vulnerability of biometric systems to these attacks. Hence, it is not yet possible to establish a common benchmark between different morph detection algorithms. In this paper, we tackle this issue proposing new metrics for vulnerability reporting, which build upon our joint experience in researching this challenging attack scenario. In addition, recommendations on the assessment of morphing techniques and morphing detection metrics are given.enBiometricsMorphingPerformance ReportingAttack Detection1617-5468