FabAuth: Printed Objects Identification Using Resonant Properties of Their Inner Structures

We present a method we propose called FabAuth for identifying 3D-printed objects, which utilizes the differences in the resonant properties of such objects. We focus on changing the internal structures of each object made through a 3D printing process to assign a unique resonant property to it even if multiple objects have the same appearance. To identify the objects, the method identifies resonant property differences by using vibration that can pass through 3D-printed objects. The method can be applied even to low-filled 3D-printed objects as long as an acoustic wave can travel through the objects from one sensor to another. To validate the method's feasibility, we conducted a preliminary experiment to confirm whether it can be applied to low-filled 3D-printed objects and found that its average classification accuracy reached 92.2%.