Computer scientists from the University of North Carolina at Chapel Hil have devised a method of bypassing face authentication systems using photos, 3D modeling software, and a VR (Virtual Reality) device.
One of the many new biometrics-based methods of authentication users is facial recognition, which uses data about a person's distinct face shape and its characteristics, like eyes, nose, mouth, and the depth and distances between them.
Facial authentication systems appeared in the 90s, but became more popular in the 2000s, as hardware and software became more powerful.
For earlier versions of face recognition systems, scientists proved that by putting a photo in front of the system's camera or video input, they could trigger the system in authenticating an attacker.
Modern facial recognition systems can't be tricked with photos anymore.
But times have changed. Since then, to mitigate this attack vector many companies providing facial recognition software started taking into account various secondary interactions such as the presence of different textures on the user's skin, asking the user to blink or perform other actions, or detecting small head movements as the user breathes.
