Unique fingerprints in 3D printing may foil adversaries
Netanel Raviv leads interdisciplinary team to create secure framework

3D printing is a simple way to create custom tools, replacement pieces and other helpful objects, but it is also being used to create untraceable firearms, such as ghost guns, like the one implicated in the late 2024 killing of UnitedHealthcare CEO Brian Thompson.
Netanel Raviv, assistant professor of computer science & engineering in the McKelvey School of Engineering at Washington University in St. Louis, led a team from the departments of Computer Science & Engineering and Biomedical Engineering that has developed a way to create an embedded fingerprint in 3D-printed parts that would withstand the item being broken, allowing authorities to gain information for forensic investigation, such as the identity of the printer or the person who owns it and the time and place of printing. The research will be presented at the USENIX Security Symposium Aug. 13-15, 2025, in Seattle. First authors of the paper are Canran Wang and Jinweng Wang, who earned doctorates in computer science in 2024 and 2025, respectively.
Fingerprinting in 3D printing embeds unique, traceable data, such as timestamps, geolocations and printer identification, into each item and allow items to be traced to the creator. While there are multiple ways to create fingerprints, none have looked at how these fingerprints may stand up to someone who tampers with or breaks the item into pieces.
Raviv’s team developed mathematical techniques to embed information into 3D printed objects in a robust way and coupled them with security mechanisms to enforce 3D-printers to embed those codes in the objects they print. The team’s framework, Secure Information Embedding and Extraction, or SIDE, uses break-resilient, loss-tolerant embedding techniques that stand up against adversaries and acts as a security mechanism.
The technique is built on research Raviv and his student presented in July 2024 at the IEEE International Symposium on Information Theory. That research focused on creating a mathematical framework for an encoder that would recover original information bits from fragments of broken 3D printed objects resulting from adversarial tampering.
“This work opens up new venues for protecting the public from the harmful aspects of 3D printing via a combination of mathematical contributions and new security mechanisms,” Raviv said. “While SIDE has limitations in defending against resourceful attackers with strong expertise in 3D printing, it significantly raises the level of sophistication, prior knowledge and expertise required from the adversary to remain undetected after committing the crime.”
Wang C, Wang J, Zhou M, Pham V, Hao S, Zhou C, Zhang N, Raviv N. Secure Information Embedding in Forensic 3D Fingerprinting. Presented at the USENIX Security Symposium Aug. 13–15, 2025. https://arxiv.org/abs/2403.04918
Funding for this research was provided by the National Science Foundation (CNS-2223032, CNS-2038995, CNS-223863) and the Army Research Office (W911NF-24-1-0155).