Preventing manipulation in automated face recognition

From unlocking smartphones to speeding up airport security checks: the use of automated face recognition for personal identification continues to grow. But this authentication method is vulnerable to morphing attacks: criminals can misuse it by melding two different facial images into one. A single passport featuring a photograph manipulated this way can then be used by two different people. Together with their partners, Fraunhofer research teams are developing a system that foils this type of attack using machine learning methods.

from News on Artificial Intelligence and Machine Learning https://ift.tt/2nsUko2

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