  Additive Manufacturing (AM, or 3D printing) is a novel manufacturing
technology that is being adopted in industrial and consumer settings. However,
the reliance of this technology on computerization has raised various security
concerns. In this paper we address sabotage via tampering with the 3D printing
process. We present an object verification system using side-channel
emanations: sound generated by onboard stepper motors. The contributions of
this paper are following. We present two algorithms: one which generates a
master audio fingerprint for the unmodified printing process, and one which
computes the similarity between other print recordings and the master audio
fingerprint. We then evaluate the deviation due to tampering, focusing on the
detection of minimal tampering primitives. By detecting the deviation at the
time of its occurrence, we can stop the printing process for compromised
objects, thus save time and prevent material waste. We discuss impacts on the
method by aspects like background noise, or different audio recorder positions.
We further outline our vision with use cases incorporating our approach.
