Abstract
Outsourced Additive Manufacturing (AM) exposes sensitive design data to external malicious actors. Even with end-to-end encryption between the design owner and 3D-printer, side-channel attacks can be used to bypass cyber-security measures and obtain the underlying design. In this paper, we develop a method based on the power side-channel that enables accurate design reconstruction in the face of full encryption measures without any prior knowledge of the design. Our evaluation on a Fused Deposition Modeling (FDM) 3D Printer has shown 99 % accuracy in reconstruction, a significant improvement on the state of the art. This approach demonstrates the futility of pure cyber-security measures applied to Additive Manufacturing.
| Original language | American English |
|---|---|
| Title of host publication | Proceedings of 2021 24th International Symposium on Research in Attacks, Intrusions and Defenses, RAID 2021 |
| Pages | 135-147 |
| Number of pages | 13 |
| ISBN (Electronic) | 9781450390583 |
| DOIs | |
| State | Published - 6 Oct 2021 |
| Event | 24th International Symposium on Research in Attacks, Intrusions and Defenses, RAID 2021 - Virtual, Online, Spain Duration: 6 Oct 2021 → 8 Oct 2021 |
Publication series
| Name | ACM International Conference Proceeding Series |
|---|
Conference
| Conference | 24th International Symposium on Research in Attacks, Intrusions and Defenses, RAID 2021 |
|---|---|
| Country/Territory | Spain |
| City | Virtual, Online |
| Period | 6/10/21 → 8/10/21 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
Keywords
- 3D Printing
- Additive Manufacturing
- IP Theft.
- Intellectual Property Theft
- Side-Channel Attack
All Science Journal Classification (ASJC) codes
- Software
- Human-Computer Interaction
- Computer Vision and Pattern Recognition
- Computer Networks and Communications
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