Detecting sabotage attacks in additive manufacturing using actuator power signatures

Abstract

Additive manufacturing (AM), a.k.a. 3D printing is increasingly used to manufacture functional parts of safety-critical systems. The AM's dependence on computerization raises the concern that the AM process can be tampered with, and a part's mechanical properties sabotaged. To address this threat, we propose a novel approach for detecting sabotage attacks based on trusted monitoring of the current delivered to each printer motor. The proposed approach offers numerous advantages: 1) it is non-invasive in a time-critical process, 2) it can be retrofitted in legacy systems, and 3) it can be air-gapped from the computerized components of the AM process, making simultaneous compromise more difficult. We evaluated the approach on five categories of toolpath command-level manipulations that impact the geometry of the 3D printed object. Our evaluation showed that all but one tested category of attacks can be reliably detected, even if a single toolpath command is modified.