&nbsp;Scientists have developed an artificial intelligence tool that can synthesize fake human fingerprints and potentially fool biometric authentication systems. Fingerprint authentication systems are a widely trusted, ubiquitous form of biometric authentication, deployed on billions of smartphones and other devices worldwide.<br />” <br />”However, researchers from New York University (NYU) in the US revealed a surprising level of vulnerability in these systems. Using a neural network, they evolved a fake fingerprint that could fool biometric authentication for one in five people.<br />” <br />”Much the way that a master key can unlock every door in a building, these Deep Master Prints use artificial intelligence to match a large number of prints stored in fingerprint databases and could thus theoretically unlock a large number of devices.<br />” <br />”The work builds on earlier research led by Nasir Memon, professor at NYU. Memon, who coined the term &quot;Master Print,&quot; described how fingerprint-based systems use partial fingerprints, rather than full ones, to confirm identity.&nbsp;<br />” <br />”<br />”<span style="color: #222222;">Researchers took this concept further, training a machine-learning algorithm to generate synthetic fingerprints as Master Prints. Memon said that these experiments demonstrate the need for multi-factor authentication and should be a wake-up call for device manufacturers about the potential for artificial fingerprint attacks.</span><br />