NexID ENHANCES FAKE-FINGER-DETECTION SOLUTION FOR EMBEDDED FINGERPRINT-SENSOR SYSTEMS
Breakthrough achieves improved speed, processing efficiency, security, convenience
TAMPA, Fla. – Sept. 16, 2014 – NexID Biometrics LLC, whose spoof-mitigation technology boosts protection in applications with critical security-authentication needs, today announced an enhanced fake-finger-detection solution for both embedded fingerprint-sensor systems and those yet to be introduced. The enhancement stems from a significant breakthrough in speed and processing efficiency.
The company, based in Potsdam, N.Y., announced the new software capabilities at the Global Identity Summit being held in the Tampa Convention Center this week. The newly enhanced NexID software is available now for custom deployments.
By completely overhauling its software’s capabilities, NexID has produced a targeted solution that’s ideal for both mobile devices with fingerprint sensors, including smartphones from Apple and Samsung that have been proven vulnerable to spoofing, and embedded modules — such as ATMs and terminals for entry access, time and attendance, and point of sale – which combine sensor and microprocessor controllers.
NexID achieved the breakthrough by redesigning its software for integration with embedded “match-on-chip” implementations where matching and fake-finger-detection software execute on the same processor that controls the fingerprint sensor’s image-capture, enrollment and authentication operations. Delivering high levels of security and convenience was another goal.
“The breakthrough outcome of our newest version is that NexID’s fake-finger-detection technology was re-architected to execute the software’s full feature set of analysis and spoof mitigation while running on embedded processors with far less computing performance and resources – such as slower processors, limited code space and data-storage constraints — than traditional desktops, laptops, and even high-end mobile devices,” said Mark Cornett, NexID’s chief operating officer.
“We’re talking about going from processor clock speeds of GHz down to MHz, multi-core processors down to single-core, and from Mb of memory down to Kb of memory. To accomplish this, we created new and innovative techniques for image enhancement, feature extraction and statistical analysis to execute our fake-finger-detection algorithms in a resource-limited environment,” Cornett said. “These techniques have resulted in fake-finger-detection performance that matches our best performing implementations, while maintaining processing times that meet user-convenience thresholds.”
He said many of the devices addressed by the upgrade in NexID software are used in situations where the person whose identity is being authenticated is alone and unsupervised, although perhaps monitored by camera, and is therefore more capable of covertly spoofing the fingerprint sensor than if he or she were in a more observed or monitored situation such as a border crossing or security-related airport kiosk.
Depending on the device or application, NexID’s fake-finger-detection solution could be used to supplement other factors of authentication, such as pins and passwords, or to replace pins and passwords as a more convenient form of authentication, such as unlocking a mobile device or using an ATM, Cornett said.
As a technology-agnostic solution, other benefits of NexID’s upgraded fake-finger detection software include that it is less costly than hardware-based solutions; requires no additional space or hardware requirements, is field upgradeable, with no need to replace hardware and gives users the flexibility to choose their own thresholds of fake-finger detection based on the requirements of particular applications.
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