If you thought your prints were anonymous think again. Researchers at the University of Illinois Urbana-Champaign have been able to use AI tools to trace the printer with a “98% accuracy from just 1 square millimeter of the part’s surface.”
King’s research group developed an AI model to identify production fingerprints from photographs taken with smartphone cameras. The AI model was developed on a large data set, comprising photographs of 9,192 parts made on 21 machines from six companies and with four different fabrication processes. When calibrating their model, the researchers found that a fingerprint could be obtained with 98% accuracy from just 1 square millimeter of the part’s surface.
“These manufacturing fingerprints have been hiding in plain sight,” King said. “There are thousands of 3D printers in the world, and tens of millions of 3D printed parts used in airplanes, automobiles, medical devices, consumer products, and a host of other applications. Each one of these parts has a unique signature that can be detected using AI.”
Original paper in Nature: Additive manufacturing source identification from photographs using deep learning
More from Hackster.io and XDA
from Adafruit Industries – Makers, hackers, artists, designers and engineers! https://ift.tt/pdBSzsv
via IFTTT
Комментариев нет:
Отправить комментарий