Secure Information Embedding and Extraction in Forensic 3D Fingerprinting

• URL: http://arxiv.org/abs/2403.04918v3
• Date: Wed, 12 Jun 2024 21:07:22 GMT
• Title: Secure Information Embedding and Extraction in Forensic 3D Fingerprinting
• Authors: Canran Wang, Jinwen Wang, Mi Zhou, Vinh Pham, Senyue Hao, Chao Zhou, Ning Zhang, Netanel Raviv,
• Abstract summary: The prevalence of 3D printing poses a significant risk to public safety. Several approaches have been taken to tag 3D-prints with identifying information. Known as fingerprints, this information is written into the object using various bit embedding techniques.
• Score: 15.196378932114518
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The prevalence of 3D printing poses a significant risk to public safety, as any individual with internet access and a commodity printer is able to produce untraceable firearms, keys, counterfeit products, etc. To aid government authorities in combating these new security threats, several approaches have been taken to tag 3D-prints with identifying information. Known as fingerprints, this information is written into the object using various bit embedding techniques; examples include varying the height of the molten thermoplastic layers, and depositing metallic powder with different magnetic properties. Yet, the practicality of theses techniques in real-world forensic settings is hindered by the adversarial nature of this problem. That is, the 3D-printing process is out of reach of any law enforcement agencies; it is the adversary who controls all aspects of printing and possesses the printed object. To combat these threats, law enforcement agencies can regulate the manufacturing of 3D printers, on which they may enforce a fingerprinting scheme, and collect adversarially tampered remains (e.g., fragments of a broken 3D-printed firearm) during forensic investigation. Therefore, it is important to devise fingerprinting techniques so that the fingerprint could be extracted even if printing is carried out by the adversary. To this end, we present SIDE (Secure Information Embedding and Extraction), a fingerprinting framework that tackles the adversarial nature of forensic fingerprinting in 3D prints by offering both secure information embedding and secure information extraction.

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