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

• URL: http://arxiv.org/abs/2607.00186v1
• Date: Tue, 30 Jun 2026 21:07:55 GMT
• Title: A Non-Line-of-Sight, Multi-Modality-based Side-Channel IP Theft Attack on Additive Manufacturing Using Dual Smartphones
• Abstract summary: Additive Manufacturing (AM) has revolutionized major sectors, including aerospace, automotive, and healthcare, by enabling adjustable production.<n>As the usage of AM increases, so does the risk of Intellectual Property leakage during the printing process due to side-channel emissions.<n>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.<n>This paper presents a side-channel attack that addresses the noted limitations by using two smartphones' internal sensors.
• Score: 4.2028398139835135
• License: http://creativecommons.org/publicdomain/zero/1.0/
• 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.

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