Image: Motherboard
Researchers at New York University and University of Michigan used a AI generative adversarial network (GAN) to generate a set of master fingerprints that can fool low security fingerprint scanners 76% of the time. At more realistic security levels, the master fingerprints can are falsly matched by sensors 22% of the time.
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