In This Article:
Facephi achieves outstanding results in RIVTD Track 3 Evaluation from Department of Homeland Security (DHS)1 in the USA
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This evaluation assessed the accuracy and robustness of biometric authentication systems in detecting presentation attacks.
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Facephi obtained an exceptionally low Bona Fide Presentation Classification Error Rate (BPCER) of under 0.2% in its RIVTD evaluation.
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This ultra-low error rate translates into high accuracy in detecting genuine users, minimized false rejections, and enhanced security against fraudulent identity attacks.
Alicante, March 13th, 2025 - Facephi Biometría, SA (BME Growth: FACE; Euronext Growth Paris: ALPHI) (“Facephi” or the “Company”), a Spanish tech leader in global digital identity protection and verification, has achieved outstanding results in the Remote Identity Validation Technology Demonstration (RIVTD) Track 3: Face Liveness Detection, an initiative led by the U.S. Department of Homeland Security (DHS) Science and Technology Directorate (S&T).
DHS RIVTD Track 3: Pioneering the Future of Remote Identity Validation
The RIVTD initiative, developed in collaboration with the Transportation Security Administration (TSA), Homeland Security Investigations Forensic Laboratory, and the National Institute of Standards and Technology (NIST), aims to objectively measure the performance of remote identity validation systems. Track 3 specifically evaluates face liveness detection technologies in their ability to differentiate legitimate users from attackers attempting impersonation.
With the increasing use of online identity verification for government services, banking, and digital platforms, the RIVTD test plays a crucial role in setting industry benchmarks for secure and user-friendly biometric authentication. By participating in this evaluation, Facephi demonstrates its commitment to developing cutting-edge fraud prevention solutions aligned with emerging security standards.
Facephi’s Presentation Attack Detection: Unmatched Accuracy and Robustness
Facephi’s participation in RIVTD Track 3 focused on the assessment of video-based presentation attack detection across multiple scenarios. The evaluation tested biometric authentication algorithms using selfies captured on leading smartphone models and subjected them to three levels of attacks:
(a) Paper printouts and screen display,
(b) Paper masks and video playback on a screen, and
(c) Advanced attacks requiring specialized hardware and significant resource investment.
Facephi’s proprietary algorithm achieved outstanding accuracy, excelling in all attack scenarios. Importantly, the evaluation confirmed that Facephi’s technology maintains fairness across demographic groups, ensuring a fair and unbiased user experience.