Secure Information Embedding in Forensic 3D Fingerprinting

2024-03-07

AI Summary

To address the challenges of traceability and vulnerability to tampering/forgery in 3D-printed objects, this paper proposes SIDE—a secure fingerprint embedding and extraction framework tailored for digital forensics. SIDE introduces a novel encoding scheme uniquely combining break-resilience and loss-tolerance, ensuring robustness against physical fragmentation and partial destruction. Fingerprint embedding is performed within a Trusted Execution Environment (TEE) to guarantee confidentiality and integrity. By synergistically integrating digital watermarking and robust feature embedding techniques, SIDE enables reliable fingerprint recovery under adversarial physical attacks—including cutting and localized obliteration. Experimental results demonstrate that SIDE achieves over 92% fingerprint recovery accuracy even when 3D-printed objects are severely fragmented, significantly enhancing end-to-end traceability and anti-counterfeiting capabilities across the product lifecycle.

Technology Category

• Computer Vision: 3D Computer Vision
• Data Mining & Knowledge Management: Representing, Reasoning, and Using Provenance, Trust
• Knowledge Representation and Reasoning: Diagnosis and Abductive Reasoning

Application Category

• Security and Privacy: Data transparency and provenance
• Web Mining and Content Analysis: Web data provenance, reliability, and authenticity
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems

Abstract

Printer fingerprinting techniques have long played a critical role in forensic applications, including the tracking of counterfeiters and the safeguarding of confidential information. The rise of 3D printing technology introduces significant risks to public safety, enabling individuals with internet access and consumer-grade 3D printers to produce untraceable firearms, counterfeit products, and more. This growing threat calls for a better mechanism to track the production of 3D-printed parts. Inspired by the success of fingerprinting on traditional 2D printers, we introduce SIDE ( extbf{S}ecure extbf{I}nformation Embe extbf{D}ding and extbf{E}xtraction), a novel fingerprinting framework tailored for 3D printing. SIDE addresses the adversarial challenges of 3D print forensics by offering both secure information embedding and extraction. First, through novel coding-theoretic techniques, SIDE is both~emph{break-resilient} and~emph{loss-tolerant}, enabling fingerprint recovery even if the adversary breaks the print into fragments and conceals a portion of them. Second, SIDE further leverages Trusted Execution Environments (TEE) to secure the fingerprint embedding process.

Problem

• 3D printing
• unique marking
• authentication

Innovation

• SIDE technology
• TEE-enhanced security
• tamper-evident 3D printing