Close

Search

Search Menu
Photonics Media Photonics Buyers' Guide Photonics EDU Photonics Spectra BioPhotonics EuroPhotonics Industrial Photonics Photonics Showcase Photonics ProdSpec Photonics Handbook
More News
share
Email Facebook Twitter Google+ LinkedIn Comments

Imaging Method Traces 3D-Printed Objects Back to Their Source

Photonics.com
Oct 2018
BUFFALO, N.Y., Oct. 19, 2018 — A University at Buffalo research team has developed a method for tracing 3D-printed objects back to the machines that printed them. PrinTracker is a 3D-printer identification system that can precisely trace the printed physical object to its source 3D printer based on the object’s “fingerprint.” 

Each layer of a 3D-printed object contains tiny wrinkles — usually measured in submillimeters — called in-fill patterns. These patterns are supposed to be uniform. However, the printer’s model type, filament, nozzle size, and other factors can cause slight imperfections in the patterns. These variations appear repeatedly and result in unique textures that can serve as a viable fingerprint on associated 3D-printed products. The texture of the printed object’s surface reflects the fingerprint that can be used to identify the device.

PrinTracker, system for tracing 3D printed materials back to their source, University at Buffalo.
An illustration of how the technology works. Courtesy of Wenyao Xu, University at Buffalo.


“3D printers are built to be the same,” professor Wenyao Xu said. “But there are slight variations in their hardware created during the manufacturing process that lead to unique, inevitable, and unchangeable patterns in every object they print.”

To test PrinTracker, the researchers created five door keys each from 14 different 3D printers. They used 10 fused deposition modeling (FDM) printers and four stereolithography (SLA) printers.

With a common scanner, the researchers created digital images of each key. They enhanced and filtered each image, identifying elements of the in-fill pattern. They then developed an algorithm to align and calculate the variations of each key to verify the authenticity of the fingerprint.

After creating a fingerprint database of the 14 3D printers, the researchers were able to match the key to its printer 99.8 percent of the time. They ran a separate series of tests 10 months later to determine if additional use of the printers would affect PrinTracker’s ability to match objects to their machines of origin. The results were the same.

The team also ran experiments involving keys damaged in various ways to obscure their identity. PrinTracker was 92 percent accurate in these tests.

Xu likens the technology to the ability to identify the source of paper documents, a practice used by law enforcement agencies and other organizations for decades. While the experiments did not involve counterfeit goods or firearms, Xu said that PrinTracker could be used to trace any 3D-printed object, including unlawful 3D-printed tools and goods, to its printer of origin.

“We’ve demonstrated that PrinTracker is an effective, robust, and reliable way that law enforcement agencies, as well as businesses concerned about intellectual property, can trace the origin of 3D-printed goods,” Xu said.

The study was presented at the Association for Computing Machinery's Conference on Computer and Communications Security, taking place Oct. 15-19, 2018, in Toronto, Canada. The paper is available for download.

GLOSSARY
stereolithography
A method of creating real three-dimensional models by using lasers driven by CAD software. In contrast to the normal practice of removing material, this process polymerizes a liquid to quickly produce shapes that are untouched by human hands or cutting tools. Also known as three-dimensional imaging and three-dimensional modeling.
Research & TechnologyeducationUniversity at BuffaloAmericasmaterialsimagingdefensesecurityConsumer3d printingstereolithographyscanning technologyPrinTrackermanufacturing

Comments
Terms & Conditions Privacy Policy About Us Contact Us
back to top
Facebook Twitter Instagram LinkedIn YouTube RSS
©2018 Photonics Media, 100 West St., Pittsfield, MA, 01201 USA, info@photonics.com

Photonics Media, Laurin Publishing
x We deliver – right to your inbox. Subscribe FREE to our newsletters.
We use cookies to improve user experience and analyze our website traffic as stated in our Privacy Policy. By using this website, you agree to the use of cookies unless you have disabled them.