A variety of materials and methods, from the inexpensive to the very sophisticated, can be used to circumvent traditional fingerprint identification systems. Called “spoofs”, some of these fake fingerprints are so thin and colorless that they can even be used, undetected, in access control environments that have trained attendants.
Lumidigm’s patent-protected liveness detection capability looks beyond the surface of the skin and can discriminate between the features of live skin and copies of those features in a fraction of a second. Multispectral imaging goes beyond conventional, contact-oriented measurements to deliver not only superior real world biometric performance but the best liveness detection capability in the industry.
Lumidigm’s liveness detection is built from cutting-edge machine learning algorithms and can be updated as new spoofs are identified. Unlike any other fingerprint technology, this “learning” capability allows Lumidigm fingerprint sensors to keep up with new threats.
V-Series fingerprint scanners have Premium liveness detection which combines a low live-finger rejection rate with the best fake finger detection capability on the market. Premium liveness detection from Lumidigm provides protection from published and unpublished methods of producing and using finger copies that will defeat conventional fingerprint sensors.
Currently, V-Series Premium liveness detection has been proven effective against over fifty-seven materials and material variations including glues, silicones, gelatins, latex, thin film tapes, photocopies, plastics, Play-Doh, waxes, and latent print activation.
It is important to note that all the published literature on making finger copies and testing spoof protection is based on copies that are made with a cooperative subject. While collecting a latent print from an uncooperative subject is certainly possible, creating a copy of such a print that is of a high enough quality to match the subject’s print and defeat liveness detection is very difficult.
Spoof Detection Schemes (801.8 KiB)
This whitepaper provides an overview of methods of attacking biometric systems and presents a fingerprint study.