NexID upgrades fake-finger-detection solution to boost anti-spoofing accuracy to nearly 100 percent
The company said that version 1.2 of its SDK, aimed at initial deployments starting next month, improves the accuracy rate range from 96.5 percent to 99.5 percent in spotting fake identification attempts across a range of fingerprint-sensor types, such as touch or swipe, and technologies, including optical and capacitance.
NexID said that the boost in performance was achieved without having a major impact on computing time or resources.
“Our ongoing research has yielded additional fingerprint-imaging features that are highly effective in differentiating images captured from authentic versus fake fingerprints,” said Mark Cornett, chief operating officer at NexID. “In essence, we have expanded our portfolio of fingerprint-imaging features and that translates into higher accuracy.”
The new SDK’s equal error rates, which is the inverse of accuracy in correctly identifying a spoof image or not, have decreased from 0.5 to 3.5 percent when compared to the previous version, said Cornett.
“We continue to explore ways to reduce equal error rates toward zero so that customers who deploy fingerprint-identification sensors can have complete confidence that authentications of the people using the sensors are accurate,” Cornett said. “We’re not aware of any software-based, fingerprint spoofing-mitigation technology today that’s more rigorous than NexID’s latest software improvement.”
Previously reported, NexID Biometrics LLC completely overhauled its software capabilities, making its solution applicable to fingerprint sensors in both mobile devices and embedded modules.
With the improved accuracy in version 1.2 of the SDK and these recent enhancements enabled by its software redesign, NexID’s fake finger detection solution is now available across the entire range of fingerprint sensor devices.