A Non-Line-of-Sight, Multi-Modality-based Side-Channel IP Theft Attack on Additive Manufacturing Using Dual Smartphones

2026-06-30

AI Summary

This work addresses the threat of intellectual property theft in additive manufacturing via side-channel leakage, a challenge inadequately mitigated by existing approaches due to low G-code reconstruction fidelity, short attack range, and reliance on specialized hardware. The authors propose a dual-smartphone-based, multimodal non-line-of-sight attack framework that leverages built-in acoustic and magnetic sensors to simultaneously capture side-channel emissions from a distance of 60 cm, enabling high-fidelity G-code reverse engineering without custom equipment. By fusing multimodal sensor data with a novel reconstruction algorithm, the method achieves 98.89% instruction-level accuracy and demonstrates strong transferability and practicality across diverse 3D printer models and environmental conditions.

Abstract

Additive Manufacturing (AM) has revolutionized major sectors, including aerospace, automotive, and healthcare, by enabling adjustable production. As the usage of AM increases, so does the risk of Intellectual Property (IP) leakage during the printing process due to unintended side-channel emissions. Current studies and attack scenarios on 3D printers face three challenges: low success and accuracy rates in final G-code reconstruction, limited distance range for attacking the 3D printer's IP, and reliance on specialized, overt data-collection tools. This paper presents a side-channel attack that addresses the noted limitations by using two smartphones' internal sensors. We position the smartphones 60 cm away in a non-line-of-sight setup to collect the 3D printer's acoustic and magnetic emissions. Our attack successfully reconstructs the G-code commands of the final objects at a rate of 98.89% on command-level reconstruction accuracy. Additionally, we evaluate the transferability of our attack strategy by applying it to another 3D printer in a different environment. Our proven unauthorized access to the reconstructed G-code and thus to the IP of the AM system indicates the security weaknesses in 3D printing, highlighting the need for mitigating side-channel attacks.

Problem

• Additive Manufacturing
• Side-Channel Attack
• Intellectual Property Theft
• Non-Line-of-Sight
• G-code Reconstruction

Innovation

• Non-Line-of-Sight
• Multi-Modality
• Side-Channel Attack
• Additive Manufacturing
• Smartphone Sensors