"Preventing Manipulation in Automated Face Recognition"

The adoption and implementation of automated face recognition continues to increase. However, this method of authentication remains vulnerable to morphing attacks in which different facial images are merged together to create a fake image. A photo stored in a biometric passport that has been altered in such a manner can allow two different people to use the same passport. A team of researchers from the Fraunhofer Institute and the Heinrich Hertz Institute are working on developing a process that uses machine learning methods to prevent the success of morphing attacks in a project called ANANAS (Anomaly Detection for Prevention of Attacks on Authentication Systems Based on Facial Images). This article continues to discuss the biometric facial recognition process, the execution of morphing attacks, and the research project aimed at preventing such attacks.

TechXplore reports "Preventing Manipulation in Automated Face Recognition"