Precise BioLive™ by Precise Biometrics identifies fake fingerprints by analyzing image differences between live and spoof fingerprints. It uses machine learning technology to accurately distinguish real fingerprints from fake ones, regardless of the spoofing method used. BioLive can be integrated with any fingerprint sensor in mobile or desktop environments without requiring additional hardware. It is upgradable to counter emerging spoof threats and can be implemented independently of fingerprint matching algorithms. BioLive is also integrated with the Precise BioMatch Mobile solution as part of Precise’s liveness verification modules. The integration allows mobile device OEMs to meet security standards in ecosystems like Android, FIDO, and Windows Biometric Framework. BioLive effectively detects fake fingerprints by analyzing image differences between live and spoof fingerprints. The algorithms utilize image processing and statistical analysis of characteristics captured by the fingerprint sensor. It exploits differences between real and fake fingers through imperfections in the image from spoof attacks. BioLive is sensor technology agnostic and offers tailored security for specific hardware configurations. A dynamic spoof detection threshold allows configuration of the security level to meet application requirements, balancing convenience (low False Rejection Rate, FRR) and security (low False Acceptance Rate, FAR).
