PrinTracker: Fingerprinting 3D Printers using Commodity Scanners
Zhengxiong Li, Aditya Singh Rathore, Chen Song, Sheng Wei, Yanzhi Wang, Wenyao Xu
Abstract
As 3D printing technology begins to outpace traditional manufacturing, malicious users increasingly have sought to leverage this widely accessible platform to produce unlawful tools for criminal activities. Therefore, it is of paramount importance to identify the origin of unlawful 3D printed products using digital forensics. Traditional countermeasures, including information embedding or watermarking, rely on supervised manufacturing process and are impractical for identifying the origin of 3D printed tools in criminal applications. We argue that 3D printers possess unique fingerprints, which arise from hardware imperfections during the manufacturing process, causing discrepancies in the line formation of printed physical objects. These variations appear repeatedly and result in unique textures that can serve as a viable fingerprint on associated 3D printed products. To address the challenge of traditional forensics in identifying unlawful 3D printed products, we present PrinTracker, the 3D printer identification system, which can precisely trace the physical object to its source 3D printer based on its fingerprint. Results indicate that PrinTracker provides a high accuracy using 14 different 3D printers. Under unfavorable conditions (e.g. restricted sample area, location and process), the PrinTracker can still achieve an acceptable accuracy of 92%. Furthermore, we examine the effectiveness, robustness, reliability and vulnerability of the PrinTracker in multiple real-world scenarios.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Cited by top-tier papers7
- Demon in the Variant: Statistical Analysis of DNNs for Robust Backdoor Contamination DetectionDi Tang, XiaoFeng Wang, Haixu Tang, Kehuan ZhangUSENIX Security 2021 · 242 citations
- G-ID: Identifying 3D Prints Using Slicing ParametersMustafa Doga Dogan, Faraz Faruqi, Andrew Day Churchill, Kenneth Friedman et al.CHI 2020 · 46 citations
- WaveSpy: Remote and Through-wall Screen Attack via mmWave SensingZhengxiong Li, Fenglong Ma, Aditya Singh Rathore, Zhuolin Yang et al.S&P 2020 · 40 citations
- "Get in Researchers; We're Measuring Reproducibility": A Reproducibility Study of Machine Learning Papers in Tier 1 Security ConferencesDaniel Olszewski, Allison Lu, Carson Stillman, Kevin Warren et al.CCS 2023 · 19 citations
- Reliable Digital Forensics in the Air: Exploring an RF-based Drone Identification SystemZhengxiong Li, Baicheng Chen, Xingyu Chen, Chenhan Xu et al.UbiComp 2022 · 15 citations
Builds on9
- Fingerprinting Electronic Control Units for Vehicle Intrusion DetectionKyong-Tak Cho, Kang G. ShinUSENIX Security 2016 · 524 citations
- discovRE: Efficient Cross-Architecture Identification of Bugs in Binary CodeSebastian Eschweiler, Khaled Yakdan, Elmar Gerhards-PadillaNDSS 2016 · 342 citations
- Viden: Attacker Identification on In-Vehicle NetworksKyong-Tak Cho, Kang G. ShinCCS 2017 · 218 citations
- Who's in Control of Your Control System? Device Fingerprinting for Cyber-Physical SystemsDavid Formby, Preethi Srinivasan, Andrew M. Leonard, Jonathan D. Rogers et al.NDSS 2016 · 171 citations
- Tracking Mobile Web Users Through Motion Sensors: Attacks and DefensesAnupam Das, Nikita Borisov, Matthew CaesarNDSS 2016 · 145 citations
Related papers
- SI3DP: Source Identification Challenges and Benchmark for Consumer-Level 3D Printer ForensicsBo Seok Shim, Yoo Seung Shin, Seong-Wook Park, Jong-Uk HouACM MM 2021 · 4 citations
- Secure Information Embedding in Forensic 3D FingerprintingCanran Wang, Jinwen Wang, Mi Zhou, Vinh Pham et al.USENIX Security 2025
- See No Evil, Hear No Evil, Feel No Evil, Print No Evil? Malicious Fill Patterns Detection in Additive ManufacturingChristian Bayens, Tuan Le, Luis Garcia, Raheem A. Beyah et al.USENIX Security 2017 · 53 citations
- SepMark: Deep Separable Watermarking for Unified Source Tracing and Deepfake DetectionXiaoshuai Wu, Xin Liao, Bo OuACM MM 2023 · 74 citations
- Tracing the Origin of Adversarial Attack for Forensic Investigation and DeterrenceHan Fang, Jiyi Zhang, Yupeng Qiu, Jiayang Liu et al.ICCV 2023 · 3 citations
