Access — through national borders, into buildings or physical plants, and into electronic devices such as PCs and networks — is increasingly unsupervised. Security, labor costs and convenience often necessitate the use of biometric access control methods such as fingerprint verification.
Unfortunately, conventional optical fingerprint sensors are easily circumvented. Based on total internal reflectance (TIR), they capture only the image of the fingerprint ridge surfaces that come into contact with the sensor. These ridges are easy to imitate using common household products and ingredients.
A variety of materials, from the inexpensive to the very sophisticated, can be used to circumvent traditional fingerprint identification systems. Some of these materials are so thin and colorless that they can even be used, undetected, in access control environments that have trained attendants. For example, a gummy bear candy that costs a few cents can make a very accurate fingerprint that will “spoof” a traditional fingerprint imaging device.
Lumidigm’s multispectral imaging technology uses multiple illumination wavelengths rather than the monochromatic illumination used in TIR imaging. In addition, polarizers may be used to emphasize the light that penetrates the surface of the skin and undergoes multiple scattering events before emerging from the skin toward the imaging array. This ability to detect subsurface features of the fingerprint enables Lumidigm technology to detect spoofs.
Lumidigm’s multispectral imaging technology can detect living flesh from non-living flesh or other organic or synthetic materials. The figure at the right shows an analysis of the surface and sub-surface spectral differences between a living finger and a prosthetic. These differences between the spectral characteristics are known and can be used to detect spoofs.
Further, since multispectral imaging technology observes the internal structures that conform to and dictate the external fingerprint ridge patterns, internal details can be compared to the surface pattern. Multispectral imaging technology from Lumidigm can verify that the “internal fingerprint” matches the external one.
Lumidigm liveness detection is built from cutting-edge machine learning algorithms. Using these algorithms and the wealth of information available from multispectral fingerprint images, Lumidigm’s liveness detection capabilities can be updated if new spoofs are identified. Unlike any other fingerprint technology, this “learning” capability allows Lumidigm fingerprint sensors to keep up with new threats.
Lumidigm’s multispectral imaging technology is hard to fool. The inexpensive and readily-available films and prostheses that easily defeat conventional fingerprint devices are rendered ineffective against Lumidigm technology.
Spoof Detection Schemes (595.6 KiB)
This whitepaper provides an overview of methods of attacking biometric systems and presents a fingerprint study.
