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arXiv · 2606.13952

Side-Channel Attacks Survive Noise Cancellation in 3D Printers

Eric Yocam·Varghese Vaidyan·Micah Flack·Gurcan Comert·Judith L. Mwakalonge
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Abstract

Active Motor Noise Cancellation (AMNC) is a noise-reduction feature shipped in commercial fused deposition modeling (FDM) 3D printers. Because it suppresses the acoustic emissions that side-channel attacks exploit, it has security-relevant side effects, though we find no evidence it was designed as a security control. We present a duration-controlled evaluation of side-channel leakage on AMNC-equipped hardware, using a public dataset of 144 synchronized acoustic and vibration recordings from two Bambu Lab printers across 12 object classes. Spectral analysis confirms suppression is measurably active: the motor-resonance band rises only 4.92 dB above its background-relative baseline during printing. Leakage nonetheless survives it. Acoustic classification is at chance for 30-second windows (11.11%, permutation p = 0.188) but reaches 27.08% on a duration-clean 60-second window and 40.28% under distributed sampling, against an 8.33% baseline: the channel is suppressed within short windows, not eliminated. The dominant discriminator, however, is print duration itself, which classifies at 63.89% (95% CI [55.78, 71.28]) from recording length alone and is validated against sliced G-code print time at r = 0.907. Vibration carries genuine geometry information independent of duration: with the observation window equalized by truncation, classification reaches 45.83% against a 25% baseline (permutation p = 0.023). It nonetheless adds no measurable information beyond duration in paired comparison. The leak is architecture-specific, present on the core-XY device (36.11%) and indistinguishable from chance on the bed-slinger (13.89%), and a consumer handset recovers as much as a mounted accelerometer (25.00% vs 26.39%). Noise cancellation raises the observation time an acoustic attacker requires without eliminating the channel, and leaves print duration entirely untouched.

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Eric Yocam, Varghese Vaidyan, Micah Flack, Gurcan Comert, Judith L. Mwakalonge. 2026-06-11. Side-Channel Attacks Survive Noise Cancellation in 3D Printers. https://doi.org/10.1109/access.2026.3727190

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