Unique 'fingerprints' can help track 3D-printed guns

Scientists claim to have developed the first accurate method to identify which machine a 3D-printed object came from, paving the way for law enforcement agencies to track the origin of printed guns, counterfeit products and other goods.

According to researchers from University at Buffalo in the US, 3D-printers leave unique 'fingerprints' on its products, which can be identified by their "PrinTracker".

"3D printing has many wonderful uses, but it's also a counterfeiter's dream. Even more concerning, it has the potential to make firearms more readily available to people who are not allowed to possess them," said Wenyao Xu, an associate professor at University at Buffalo.

Like a common inkjet printer, 3D printers move back-and-forth while "printing" an object. Instead of ink, a nozzle discharges a filament, such as plastic, in layers until a three-dimensional object forms.

Each layer of a 3D-printed object contains tiny wrinkles -- usually measured in submillimetres -- 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-millimetre in-fill patterns. But the actual object has patterns that vary 5 to 10 per cent 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 said.

To test PrinTracker, researchers created five door keys each from 14 common 3D printers.

With a common scanner, the researchers created digital images of each key. From there, 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.

Having created a fingerprint database of the 14 3D printers, the researchers were able to match the key to its printer 99.8 per cent 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 machine 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 per cent 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, printer companies and other organizations for decades.

While the experiments did not involve counterfeit goods or firearms, Xu said PrinTracker can be used to trace any 3D-printed object to its printer.