# Power Consumption-based Detection of Sabotage Attacks in Additive Manufacturing

arXiv: https://arxiv.org/abs/1709.01822 · HTML: https://mlsanity.com/paper/1709.01822/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Sep 2017.

## Built on by (most cited first, 1 of 1)

- [Cyber Security in Smart Manufacturing (Threats, Landscapes Challenges)](https://mlsanity.com/paper/2304.10180/) (2023)

## Abstract (arXiv)

Additive Manufacturing (AM), a.k.a. 3D Printing, is increasingly used to manufacture functional parts of safety-critical systems. AM's dependence on computerization raises the concern that the AM process can be tampered with, and a part's mechanical properties sabotaged. This can lead to the destruction of a system employing the sabotaged part, causing loss of life, financial damage, and reputation loss. To address this threat, we propose a novel approach for detecting sabotage attacks. Our approach is based on continuous monitoring of the current delivered to all actuators during the manufacturing process and detection of deviations from a provable benign process. The proposed approach has numerous advantages: (i) it is non-invasive in a time-critical process, (ii) it can be retrofitted in legacy systems, and (iii) it is airgapped from the computerized components of the AM process, preventing simultaneous compromise. Evaluation on a desktop 3D Printer detects all attacks involving a modification of X or Y motor movement, with false positives at 0%.