FacePhi face biometrics achieve spoof attack detection standard compliance in iBeta testing
Biometric facial recognition from FacePhi has been found compliant to the ISO/IEC 30107 standard for Presentation Attack Detection (PAD) in testing by iBeta Quality Assurance. The company’s technology was found to have a 0 percent IAPMR (imposter attack presentation match rate) with a false match rate of 0 percent in an audit and testing process lasting several months, according to the announcement.
The standard consists of guidelines for submitting a biometric technology to the most effective attacks possible to defeat its security measures, FacePhi explains.
iBeta has more than 20 years of experience in analysis of the quality and security of critical software services.
FacePhi Quality Department Director Jorge Félix Iglesias says, “facial recognition is reaffirmed as the most valuable biometric tool to ensure the comfort and security of users in any area where they need to validate their identity. The way it is used avoids any contact and is simple and intuitive. This has led to a great boom in technology and, consequently, represents a push for biometric companies to work on quality standards according to demand.”
IrisGuard’s iris biometrics were recently declared compliant to the same standard by iBeta.
FacePhi continues to build out its presence in Latin America, meanwhile, with the creation of a new work unit made up of various specialists that will operate from Uruguay to provide technical support and advisory services to customers in the region.
The company says the specialized unit will assist with the implementation of new projects based on biometrics and digital onboarding, and speed up its growth in the market with professionals in biometric development and support and business development.
Argentina was noted as a growth cornerstone for FacePhi when the company’s technology was adopted by a payment app in the country in May.
Article Topics
biometric testing | biometrics | FacePhi | facial recognition | iBeta | spoof detection | standards
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