WHY THIS MATTERS IN BRIEF
Biometrics can be increasingly easily hacked, so we need to find new ways to authenticate people.
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Many people already use fingerprint recognition technology to access their smartphones, as well as obviously facial ID, but now one group of researchers wants to take this skin-deep fingerprint ID concept further, and then embed the technology into the displays of the gadgets we use. In a study published in IEEE Sensors Journal, a team of researchers in the US described a new technique that not only scans the unique pattern of a person’s fingerprint, but also the blood vessels in the persons actual fingers.
Needless to say the approach adds another layer of security to a form of identity authentication that, as was proved a while ago, can be hacked by simply printing out a picture of the users fingerprints from their selfie shots. It’s also yet another example of how technologies, like this laser I discussed recently, are increasingly able to see inside our bodies to identify and authenticate us – for whatever reasons …
Typically, a fingerprint scan, whether it’s on a smartphone or an authentication system in an office building, only accounts for 2D information that captures a person’s unique fingerprint pattern of ridges and valleys, but this 2D information could easily be replicated.
“Compared with the existing 2D fingerprint recognition technologies, 3D recognition that captures the finger vessel pattern within a user’s finger will be ideal for preventing spoofing attacks and be much more secure,” explains Xiaoning Jiang, a distinguished professor at North Carolina State University and co-author of the study.
To develop a more secure approach using 3D recognition, Jiang and his colleagues created a device that relies on ultrasound pulses. When a finger is placed upon the system, triggering a pressure sensor, a high-frequency pulsed ultrasonic wave is emitted. The amplitudes of reflecting soundwaves can then be used to determine both the fingerprint and blood vessel patterns of the person.
In an experiment, the device was tested using an artificial finger created from polydimethylsiloxane, which has an acoustic impedance similar to human tissues. Bovine blood was added to vessels constructed in the artificial finger. Through this set up, the researchers were able to obtain electronic images of both the fingerprint and blood vessel patterns with resolutions of 500 × 500 dots per inch, which they say is sufficient for commercial applications.
Intriguingly, while the blood vessel features beneath the ridges of the artificial finger could be determined, this was not the case for 40% of the blood vessels that lay underneath the valleys of the fingerprint. Jiang explains that this is because the high-frequency acoustic waves cannot propagate through the tiny spaces confined within the valleys of the fingerprint. Nevertheless, he notes that enough of the blood vessels throughout the finger can be distinguished enough to make this approach worthwhile, and that data interpolation or other advanced processing techniques could be used to reconstruct the undetected portion of vessels.
Chang Peng, a post-doc research scholar at North Carolina State University and co-author of the study, sees this approach as widely applicable.
“We envision this 3D fingerprint recognition approach can be adopted as a highly secure biometric technique for broad applications including consumer electronics, law enforcement, banking and finance, as well as smart homes,” he says, noting that this group is seeking a patent and looking for industry partners to help commercialise the technology.
Notably, the current set up using a single ultrasound inducer takes an hour or more to acquire an image, so to improve this time the team are now planning to explore how an array of ultrasonic fingerprint sensors embedded underneath a smartphones screen will perform compared to the single sensor that was used in this study. Then they aim to test the device with real human fingers, comparing the security and robustness of their technique to commercialised optical and capacitive techniques for real fingerprint recognition.