Miaxis Fingerprint Biometrics Passes iBeta Level 1 PAD Test

Published Date : 10/24/2025 

Miaxis Biometrics' fingerprint recognition system has successfully met ISO/IEC 30107-3 compliance for biometric presentation attack detection (PAD) evaluations by iBeta Quality Assurance's Level 1. The system recorded a 0% Attack Presentation Classification Error Rate (APCER) across 900 presentation attacks. 

Miaxis Biometrics, a leading provider of biometric solutions, has achieved a significant milestone by successfully passing the ISO/IEC 30107-3 compliance for biometric presentation attack detection (PAD) evaluations conducted by iBeta Quality Assurance's Level 1. This evaluation is a crucial step in ensuring the robustness and reliability of biometric systems against spoofing attacks.

Level 1 PAD testing is designed to simulate basic presentation attacks using cooperative subjects who provide high-quality biometric samples, such as photos and videos. The testing process involves alternating one bona fide presentation with three artefact attempts, totaling 150 presentation attacks and 50 genuine interactions per species, or until eight hours of testing elapsed.

The evaluation was conducted under iBeta’s accredited testing program on Miaxis’ fingerprint liveness detection software installed on the company’s proprietary SM-93s scanner, which was connected to a Windows 11 PC. The testing period ran from September 9 to September 19, 2025, and focused on detecting spoofing attempts using simple, readily available materials.

During the evaluation, the system’s responses were displayed in real time on the test interface. Successful authentication was indicated by the message “RealFinger,” while failed spoof attempts were flagged with “FakeFinger.” Across 900 presentation attacks, the Miaxis system recorded an Attack Presentation Classification Error Rate (APCER) of 0 percent, as stated in the confirmation letter from iBeta. This means that no spoofing attempts were successful. The Bona Fide Presentation Classification Error Rate (BPCER) was also measured and is detailed in the final report.

Tests to confirm compliance with the international standard for biometric presentation attack detection have increased in number in recent years, reaching an all-time high last year. This underscores the growing importance of robust liveness detection in biometric systems to prevent unauthorized access and ensure security.

Miaxis Biometrics’ achievement in passing the Level 1 PAD evaluation is a testament to the company’s commitment to innovation and security. The successful completion of this rigorous testing process not only enhances the credibility of Miaxis’ fingerprint recognition system but also provides confidence to its clients and partners in the reliability and effectiveness of the technology.

For more information about Miaxis Biometrics and their range of biometric solutions, including the SM-93s scanner, visit their official website or contact their customer support team. 

Frequently Asked Questions (FAQS): 

Q: What is ISO/IEC 30107-3 compliance?

A: ISO/IEC 30107-3 is an international standard that specifies the requirements for biometric presentation attack detection (PAD). It ensures that biometric systems can effectively detect and prevent spoofing attempts.

Q: What is Level 1 PAD testing?

A: Level 1 PAD testing is a basic level of evaluation that simulates presentation attacks using cooperative subjects and high-quality biometric samples. It is designed to test the system's ability to detect simple spoofing attempts.

Q: What is the SM-93s scanner?

A: The SM-93s is a proprietary fingerprint scanner developed by Miaxis Biometrics. It is designed to work with Miaxis’ fingerprint liveness detection software to ensure high levels of security and accuracy.

Q: What is Attack Presentation Classification Error Rate (APCER)?

A: APCER is the rate at which a biometric system incorrectly accepts presentation attacks. A 0% APCER means that the system successfully detected all spoofing attempts.

Q: Why is biometric liveness detection important?

A: Biometric liveness detection is crucial for preventing unauthorized access by ensuring that the biometric sample being presented is genuine and not a spoof. This enhances the security and reliability of biometric systems. 

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