dr0wned - Cyber-Physical Attack with Additive Manufacturing
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Abstract (arXiv)
Additive manufacturing (AM), or 3D printing, is an emerging manufacturing technology that is expected to have far-reaching socioeconomic, environmental, and geopolitical implications. As use of this technology increases, it will become more common to produce functional parts, including components for safety-critical systems. AM's dependence on computerization raises the concern that the manufactured part's quality can be compromised by sabotage. This paper demonstrates the validity of this concern, as we present the very first full chain of attack involving AM, beginning with a cyber attack aimed at compromising a benign AM component, continuing with malicious modification of a manufactured object's blueprint, leading to the sabotage of the manufactured functional part, and resulting in the physical destruction of a cyber-physical system that employs this part. The contributions of this paper are as follows. We propose a systematic approach to identify opportunities for an attack involving AM that enables an adversary to achieve his/her goals. Then we propose a methodology to assess the level of difficulty of an attack, thus enabling differentiation between possible attack chains. Finally, to demonstrate the experimental proof for the entire attack chain, we sabotage the 3D printed propeller of a quadcopter UAV, causing the quadcopter to literally fall from the sky.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 1 Sep 2016.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 1; 2024: 0; 2025: 0; 2026: 2.
4 papers.
- 2021Needle in a Haystack: Detecting Subtle Malicious Edits to Additive Manufacturing G-code Filescited by 4
- 2026Engineering Attack Vectors and Detecting Anomalies in Additive Manufacturingcited by 2
- 2023Leveraging Semantic Relationships to Prioritise Indicators of Compromise in Additive Manufacturing Systemscited by 0
- 2026Side-Channel Attacks Survive Noise Cancellation in 3D Printerscited by 0
- 2026Side-Channel Attacks Survive Noise Cancellation in 3D Printers11 Jun 2026
- 2026Engineering Attack Vectors and Detecting Anomalies in Additive Manufacturing1 Jan 2026
- 2023Leveraging Semantic Relationships to Prioritise Indicators of Compromise in Additive Manufacturing Systems6 May 2023
- 2021Needle in a Haystack: Detecting Subtle Malicious Edits to Additive Manufacturing G-code Files24 Nov 2021