In a collaborative study, researchers of US universities University at Buffallo, Rutgers University and Northeastern University developed an accurate method to trace a 3D printed object back to the machine it came from, called PrinTracker.
In the past years, developments in 3D printing have made huge strides. 3D printers have become smaller and more affordable, making the technology accessible for many people. However, while most of these commercial printers are used mainly to make object for personal use, the technology has the potential to create untraceable firearms.
These 3D printed guns are not detectable by metal detectors, but the researchers found a way to at least trace the objects back to its original printer, thanks to the 3D printer’s unique ‘fingerprint’.
3D printers commonly create objects by moving their nozzle back and forth as they print, discharging filament in the place it needs to be. Each layer of the printed object contains tiny wrinkles, measured in submillimetres, called in-fill patterns. These patterns are supposed to be uniform, but the printer’s model type, filament, nozzle size and other factors cause slight imperfections I the patterns. The result is an object that does not match its design plan exactly.
The team found that, like a fingerprint to a person, these patterns are unique and repeatable, which means they can be traced back to the 3D printer.
To test their hypothesis, the researchers created five door keys per printer, using 14 common 3D printers (10 fused deposition modelling (FDM) printers and four stereolithography (SLA) printers). With a common scanner, they created digital images of each key and identified 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.
With the database, the team was able to match the key to its printer with a 99.8 per cent accuracy. They ran a separate series of test 10 months later to determine if additional use of the printer would affect the in-fill pattern, but the results were the same. The researches also tested the PrinTracker method with damaged keys, but still could match the objects to the printer with a 92 per cent accuracy.
The method is similar to the ability to identify the source of paper document, a practice used by law enforcement agencies, printer companies and other organisations for decades. The researchers say that the method could be used for any 3D printed object, including 3D printed guns.
Image: Wenyao Xu, University at Buffalo