Using “deep learning” and AI/machine learning, researchers have created “master” fingerprints that are generated and can be used to unlock smartphones. The success rate seems to be between 1.2 percent and 22 percent for higher security fingerprint tiers:
The master prints generated by the researchers were specifically designed to target the type of fingerprint sensors found in most modern smartphones. These capacitive fingerprints scanners usually only take partial readings of fingerprints when they are placed on the sensor. This is mostly for convenience since it would be impractical to require a user to place their finger on the sensor the exact same way each time they scan their print. The convenience of partial fingerprint readings comes at the cost of security, which is convenient for a sneaky AI.
In the middle security tier, where a sensor incorrectly identifies a match 0.1 percent of the time—which the researchers described as a “realistic security option”—they were able to spoof digital fingerprints 22 percent of the time. As the researchers noted, this is a “much higher number of (impostor) matches than what the FMR would lead one to expect.”