Secure Information Embedding in Forensic 3D Fingerprinting
Canran Wang, Jinwen Wang, Mi Zhou, Vinh Pham, Senyue Hao, Chao Zhou, Ning Zhang, Netanel Raviv
摘要
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 (Secure Information EmbeDding and Extraction), 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 break-resilient and 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.
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它引用的顶会 Paper8
- Telekine: Secure Computing with Cloud GPUsTyler Hunt, Zhipeng Jia, Vance Miller, Ariel Szekely 等NSDI 2020 · 被引用 108 次
- RT-TEE: Real-time System Availability for Cyber-physical Systems using ARM TrustZoneJinwen Wang, Ao Li, Haoran Li, Chenyang Lu 等S&P 2022 · 被引用 69 次
- PrinTracker: Fingerprinting 3D Printers using Commodity ScannersZhengxiong Li, Aditya Singh Rathore, Chen Song, Sheng Wei 等CCS 2018 · 被引用 48 次
- Secure and Timely GPU Execution in Cyber-physical SystemsJinwen Wang, Yujie Wang, Ning ZhangCCS 2023 · 被引用 12 次
- IP Protection in TinyMLJinwen Wang, Yuhao Wu, Han Liu, Bo Yuan 等DAC 2023 · 被引用 6 次
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