Coding for Forensic 3D Fingerprinting.

3D printing brings about a revolution in consumption and distribution of goods, but poses a significant risk to public safety. Any individual with internet access and a commodity printer can now produce untraceable firearms (ghost guns), keys, and dangerous counterfeit products. To combat these threats, it is important to embed identifying information inside the object, so that the perpetrator could be identified if the (potentially damaged) object is confiscated or left at a crime scene. The talk will begin by surveying some existing 3D printing technologies, and presenting new and existing techniques for information embedding. Related adversarial noise patterns will be analyzed, and an abstract coding problem will be formulated. Then, our progress in solving this problem, as well as experimental proof-of-concept, will be presented.