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 that 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 observation windows (11.11%, permutation p = 0.188) but reaches 27.08% on a duration-clean 60-second window and 40.28% when sampling is distributed across the print, 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%, CI lower bound 7.72%), and a consumer handset recovers as much as a mounted accelerometer (25.00% versus 26.39%). We conclude that noise cancellation raises the observation time an acoustic attacker requires without eliminating the channel, and leaves print duration—the strongest discriminator—entirely untouched. We release all code and analysis artifacts.
| Original language | English |
|---|---|
| Journal | IEEE Access |
| Early online date | Aug 25 2026 |
| DOIs | |
| State | E-pub ahead of print - Aug 25 2026 |
Keywords
- additive manufacturing
- cyber-physical security
- noise cancellation
- print duration
- side-channel attacks
- vibration analysis
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