Globally distributed additive manufacturing is a relatively new frontier in the field of product lifecycle management. Designers are independent of additive manufacturing services, often thousands of miles apart. Manufacturing data must be transmitted electronically from designer to manufacturer to realize the benefits of such a system. Unalterable blockchain legers can record transactions between customers, designers, and manufacturers allowing each to trust the other two without needing to be familiar with each other. Although trust can be established, malicious printers or customers still have the incentive to produce unauthorized or pirated parts. To prevent this, machine instructions are encrypted and electronically transmitted to the printing service, where an authorized printer decrypts the data and prints an approved number of parts or products. The encrypted data may include G-Code machine instructions which contain every motion of every motor on a 3D printer. Once these instructions are decrypted, motor drivers send control signals along wires to the printer's stepper motors. The transmission along these wires is no longer encrypted. If the signals along the wires are read, the motion of the motor can be analyzed, and G-Code can be reverse engineered.

This thesis demonstrates such a threat through a simulated attack on a G-Code controlled device. A computer running a numeric controller and G-Code interpreter is connected to standard stepper motors. As G-Code commands are delivered, the magnetic field generated by the transmitted signals is read by a Hall Effect sensor. The rapid oscillation of the magnetic field corresponds to the stepper motor control signals which rhythmically move the motor. The oscillating signals are recorded by a high speed analog to digital converter attached to a second computer. The two systems are completely electronically isolated.

The recorded signals are saved as a string of voltage data with a matching time stamp. The voltage data is processed through a Matlab script which analyzes the direction the motor spins and the number of steps the motor takes. With these two pieces of data, the G-Code instructions which produced the motion can be recreated. The demonstration shows the exposure of previously encrypted data, allowing for the unauthorized production of parts, revealing a security flaw in a distributed additive manufacturing environment.