CyberSecurity: Machine learning can create fake fingerprints

Abstract

JUST LIKE ANY lock can be picked, any biometric scanner can be fooled. Researchers have shown for years that the popular fingerprint sensors used to guard smartphones can be tricked sometimes, using a lifted print or a person’s digitized fingerprint data. But new findings from computer scientists at New York University’s Tandon School of Engineering could raise the stakes significantly. The group has developed machine learning methods for generating fake fingerprints—called DeepMasterPrints—that not only dupe smartphone sensors but can successfully masquerade as prints from numerous different people. Think of it as a skeleton key for fingerprint-protected devices.

How this is possible?

As of now, mobile devices take when scanning a user’s fingerprint. The sensors are small enough that they can only “see” part of your finger at any given time. As such, they make some assumptions based on a snippet, which also means that fake fingerprints likely need to satisfy fewer variables to trick them.

Research Paper & References.

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Categories: biometric security, Cyber Security, cyber security news, fingerprints security

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