Is your biometric system robust to morphing attacks?

The wide deployment of biometric recognition systems has raised several concerns regarding their security. Among other threats, morphing attacks consist of the infiltration of artificial images created using biometric information of two or more subjects. These morphed images are hence positively matched to several subjects. Recent studies have shown that such images pose a concrete threat to civil security: wanted criminal offenders can use an authentic passport to enter a country with a false identity. However, there is still no quantitative manner to analyse this threat. We address this shortcoming by proposing a new framework for the evaluation of the vulnerability of biometric systems to morphing attacks. The experimental analysis on real systems based on face, iris and fingerprint shows that even systems providing high verification accuracy are vulnerable to this kind of attacks, depending on the verification threshold and the shape of the mated and non-mated score distributions.