IrisGuard iris biometrics declared compliant with ISO/IEC spoof attack detection standard by iBeta
IrisGuard’s contactless iris biometric technology has been declared Level 1 ISO/IEC 30107-3 Presentation Attack Detection (PAD) compliant by iBeta Quality Assurance on its first attempt.
The company says it is one of only two of its kind to be found compliant for its EyePay Android phone, app, and EyeCloud processing system. IrisGuard’s technology can verify and authenticate a payment from one person among millions, anywhere in the world, in less than three seconds, according to the announcement.
Advanced defense-grade countermeasures to prevent spoofing are included in all IrisGuard systems. The company developed and built in house a bespoke AI PAD engine specifically for its EyePay phone, leveraging the expertise of a leading expert designer of countermeasure topology. Further, IrisGuard commissioned an independent image specialist in the UK to attempt to defeat its system with images taken from different media, enabling the company to refine its algorithm and processes for countering presented artifacts.
“Whilst our fixed-station images have held worldwide patents since 2011 for innovative PAD detection methods, we are delighted that our independently certified EyePay Phone AI-based PAD detection brings the same quality protection to our mobile customers, complementing our secure expansion into mobile money and financial inclusion.”
iBeta claims to have the only NIST NVLAP and FIDO accredited independent biometric test lab in the world.
The EyePay platform is used to serve 2.5 million beneficiaries, distributing vital assistance to the world’s unbanked, the company says in the press release, and has processed trillions of cross-comparisons with a 0 percent error-rate.
The company also recently provided an update on the use of its refugee aid delivery platform, which has not been disrupted by physical distancing requirements.
Related Posts
Article Topics
biometric payments | biometrics | iBeta | iris biometrics | iris recognition | IrisGuard | research and development | spoof detection
Comments