Sep 25, 2017 | By Tess

A team of researchers from Michigan State University has used 3D printing to develop a realistic fingerprint model that will allow other researchers to test and improve fingerprint scanners. The ultimate goal is to make fingerprint-based security systems more difficult to crack and hack.

With the current attention on the new iPhone 8 and its facial recognition technology, it may seem like fingerprint scanners are becoming a thing of the past. This is far from true, however, as many people still rely on the simple touch of their finger to unlock their mobile devices. It is, admittedly, more discreet than a face scanning lock.

And while fingerprint scanning tech can seem like a breeze compared to typing in a passcode every time you want to check a Snapchat, there is the underlying problem that they are quite easy to break into.

As has been proven a number of times, all you really need to crack a fingerprint scanner is an image of the user’s finger, which can be translated into a 3D model and 3D printed. Anil Jain, one of the authors of the Michigan State University study, has some experience in the field.

Last year, Jain was approached by the police with a request to unlock a dead man’s phone by recreating his fingerprint. Impressively, Jain and his team were able to crack the phone in only two tries. Now, with his lab’s recent research project, the biometrics expert is aiming to help manufacturers improve their finger scanning tech.

The MSU team created the fake finger by 3D printing a mold of the highly realistic model. With the mold, the team then cast the finger from various kinds of silicone and pigments. The result is an ultra-realistic fingerprint model that can be used to establish and hopefully attain better fingerprint reading security.

As the abstract for the project reads, “We present the design and manufacturing of high fidelity universal 3D fingerprint targets, which can be imaged on a variety of fingerprint sensing technologies, namely capacitive, contact-optical, and contactless-optical. Universal 3D fingerprint targets enable, for the first time, not only a repeatable and controlled evaluation of fingerprint readers, but also the ability to conduct fingerprint reader interoperability studies.”

In other words, the 3D printed finger can be used with all three types of ID scanning methods: optical, capacitive, and ultrasound-based scanning. The first, optical scanning, is the simplest of the three and basically consists of taking a photo of the fingertip to match it with the original saved one.

The second technology, capacitive scanning, is slightly more advanced as it uses the finger’s conductivity and electrical currents to create a clearer, more accurate image of the user’s finger. The most complex (and most accurate) method is the ultrasound scanner, which emits ultrasonic pulse presses on the finger, the responses of which allow the scanner to map out the grooves and fine details of the fingerprint.

(Images: MSU)

With the highly realistic 3D printed finger, the researchers say they are now better equipped to test and compare the various 3D scanning methods. This is largely because the fake finger captures the optical, electrical, and mechanical properties of a real finger—a rare feat for a finger model.

“Our experiments conducted with PIV and Appendix F certified optical (contact and contactless) and capacitive fingerprint readers demonstrate the usefulness of universal 3D fingerprint targets for controlled and repeatable fingerprint reader evaluations and also fingerprint reader interoperability studies,” the abstract says.

Ultimately, Jain’s team hopes to help improve fingerprint-based security locks and, importantly, make them harder to crack into.

The research project was recently published under the title “Universal 3D Wearable Fingerprint Targets: Advancing Fingerprint Reader Evaluations” on the arXiv database. It is set to appear in the journal IEEE Transactions on Information Forensics and Security.



Posted in 3D Printing Application



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jeff wrote at 9/28/2017 9:54:18 AM:


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