PrinTracker: Researchers discover ways to trace 3D printed guns using 3D printer fingerprint

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Oct 16, 2018 | By Thomas

The wide release of the 3D-printed gun blueprints has become an issue for policymakers. With 3D printers, a person could download a schematic for a firearm online, and create a gun on the spot. No serial number to trace the 3D printed guns, which will become cheap and accessible for would-be criminals.

Photo illustration of how the technology works. Credit: Wenyao Xu, University at Buffalo.

Researchers at University at Buffalo, however, report they’ve found the first accurate method to help law enforcement and intelligence agencies track the origin of 3D-printed guns and counterfeit products. The technology, called “PrinTracker,” can precisely trace the physical object to its source 3D printer based on its fingerprint.

Potential untraceable 3D printed objects acquired from the crime scene

In a press release, Wenyao Xu, PhD, associate professor of computer science and engineering in UB’s School of Engineering and Applied Sciences explains part of the methodology:

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 cause slight imperfections in the patterns. The result is an object that does not match its design plan.

For example, the printer is ordered to create an object with half-millimeter in-fill patterns. But the actual object has patterns that vary 5 to 10 percent from the design plan. Like a fingerprint to a person, these patterns are unique and repeatable. As a result, they can be traced back to the 3D printer.

“3D printers are built to be the same. 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,” Xu says.

To test PrinTracker, the research team 3D printed five door keys each from 14 different commercially available 3D printers — 10 frequency division multiplexing (FDM) printers and four stereolithography (SLA) printers. The team created digital images of each key with an inkjet scanner, then enhanced each image to identify the filament pattern. They then developed an algorithm to calculate variations of each key down to the millimeter to verify the authenticity of the fingerprint. Owing to the effective comparison from the fingerprint in the pre-formed database, the physical object in forensic scenes can be precisely traced to its source 3D printer.

The system overview of PrinTracker.

According to researchers, they were able to match the key to its printer 99.8 percent of the time. They ran another round of tests 10 months later to determine if additional use of the printers would affect PrinTracker’s ability to match objects to their machine of origin. The results were the same. Researchers also ran experiments involving keys damaged in various ways to obscure their identity. PrinTracker was 92 percent accurate in these tests.

The two types of texture on a 3D printed object.

Xu hopes PrinTracker can be used to trace any 3D-printed object to its printer.

“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 says.

However, regulating guns that aren’t traditionally manufactured won’t be easy. Tracing 3D printed guns would require a record of all 3D printers being sold and information of whoever buys it. Their “fingerprints” would have to be stored in a government database. Given that only 79 million civilian guns are actually registered, which is just 9% of the total suspected guns, it might take a while before the team’s method could ever be implemented.

The “PrinTracker” study will be presented in Toronto at the Association for Computing Machinery’s Conference on Computer and Communications Security, which runs from Oct. 15-19. It includes coauthors from Rutgers University and Northeastern University.

Posted in 3D Printing Application

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