Via Bruce Schneier, researchers have developed software that can bamboozle facial-recognition software up to 60% of the time:
The work suggests that it’s possible to generate such ‘master keys’ for more than 40% of the population using only 9 faces synthesized by the StyleGAN Generative Adversarial Network (GAN), via three leading face recognition systems.
The paper is a collaboration between the Blavatnik School of Computer Science and the school of Electrical Engineering, both at Tel Aviv.
StyleGAN is initially used in this approach under a black box optimization method focusing (unsurprisingly) on high dimensional data, since it’s important to find the broadest and most generalized facial features that will satisfy an authentication system.
This process is then repeated iteratively to encompass identities that were not encoded in the initial pass. In varying test conditions, the researchers found that it was possible to obtain authentication for 40-60% with only nine generated images.
The paper contends that ‘face based authentication is extremely vulnerable, even if there is no information on the target identity’, and the researchers consider their initiative a valid approach to a security incursion methodology for facial recognition systems.
Hey, humans have evolved for 20,000 years or longer to recognize faces, and we make mistakes all the time. Maybe security software just needs more time?