From unlocking smartphones to speeding up airport security checks: the use of automated face recognition for personal identification continues to grow. But this authentication method is vulnerable to morphing attacks: criminals can misuse it by melding two different facial images into one.
A single passport featuring a photograph manipulated this way can then be used by two different people. Together with their partners, Fraunhofer research teams are developing a system that foils this type of attack using machine learning methods.
Travelers who regularly visit the USA are used to being asked to look into a camera during passport inspection. The electronic photo is instantly compared with the photo stored in the biometric passport.
In this biometric facial recognition process, a program captures the digital data of the live image and compares it with the data of the chip image in order to determine whether or not the individual facial characteristics in the photos match.
Face recognition can also be used to unlock smartphones and tablets. This method is intended to lock out unauthorized third parties and restrict access to sensitive data. But the technology is vulnerable to targeted attacks, as a variety of tests have already demonstrated.
