Turning Hearsay into Discovery: Industrial 3D Printer Side Channel Information Translated to Stealing the Object Design

The central security issue of outsourced 3D printing (aka AM: Additive Manufacturing), an industry that is expected to dominate manufacturing, is the protection of the digital design (containing the designers' model, which is their intellectual property) shared with the manufacturer. Here, we show, for the first time, that side-channel attacks are, in fact, a concrete serious threat to existing industrial grade 3D printers, enabling the reconstruction of the model printed (regardless of employing ways to directly conceal the design, e.g. by encrypting it in transit and before loading it into the printer). Previously, such attacks were demonstrated only on fairly simple FDM desktop 3D printers, which play a negligible role in manufacturing of valuable designs. We focus on the Powder Bed Fusion (PBF) AM process, which is popular for manufacturing net-shaped parts with both polymers and metals. We demonstrate how its individual actuators can be instrumented for the collection of power side-channel information during the printing process. We then present our approach to reconstruct the 3D printed model solely from the collected power side-channel data. Further, inspired by Differential Power Analysis, we developed a method to improve the quality of the reconstruction based on multiple traces. We tested our approach on two design models with different degrees of complexity. For different models, we achieved as high as 90.29~\% of True Positives and as low as 7.02~\% and 9.71~\% of False Positives and False Negatives by voxel-based volumetric comparison between reconstructed and original designs. The lesson learned from our attack is that the security of design files cannot solely rely on protecting the files themselves in an industrial environment, but must instead also rely on assuring no leakage of power, noise and similar signals to potential eavesdroppers in the printer's vicinity.

Publication Details

Journal
ArXiv.org
Published
2025-09-22
Primary Topic
COVID-19 Impact on Reproduction
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Turning Hearsay into Discovery: Industrial 3D Printer Side Channel Information Translated to Stealing the Object Design

ArXiv.org
COVID-19 Impact on Reproduction
article

Turning Hearsay into Discovery: Industrial 3D Printer Side Channel Information Translated to Stealing the Object Design

article en

Abstract

The central security issue of outsourced 3D printing (aka AM: Additive Manufacturing), an industry that is expected to dominate manufacturing, is the protection of the digital design (containing the designers' model, which is their intellectual property) shared with the manufacturer. Here, we show, for the first time, that side-channel attacks are, in fact, a concrete serious threat to existing industrial grade 3D printers, enabling the reconstruction of the model printed (regardless of employing ways to directly conceal the design, e.g. by encrypting it in transit and before loading it into the printer). Previously, such attacks were demonstrated only on fairly simple FDM desktop 3D printers, which play a negligible role in manufacturing of valuable designs. We focus on the Powder Bed Fusion (PBF) AM process, which is popular for manufacturing net-shaped parts with both polymers and metals. We demonstrate how its individual actuators can be instrumented for the collection of power side-channel information during the printing process. We then present our approach to reconstruct the 3D printed model solely from the collected power side-channel data. Further, inspired by Differential Power Analysis, we developed a method to improve the quality of the reconstruction based on multiple traces. We tested our approach on two design models with different degrees of complexity. For different models, we achieved as high as 90.29~\% of True Positives and as low as 7.02~\% and 9.71~\% of False Positives and False Negatives by voxel-based volumetric comparison between reconstructed and original designs. The lesson learned from our attack is that the security of design files cannot solely rely on protecting the files themselves in an industrial environment, but must instead also rely on assuring no leakage of power, noise and similar signals to potential eavesdroppers in the printer's vicinity.

ArXiv.org
Industry, innovation and infrastructure
Openalex Percentile: Top 35%
COVID-19 Impact on Reproduction
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.