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• W2891599753 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 their 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 vulnerabilities of the PrinTracker in multiple real-world scenarios." @default.
• W2891599753 created "2018-09-27" @default.
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• W2891599753 date "2018-10-15" @default.
• W2891599753 modified "2023-10-09" @default.
• W2891599753 title "PrinTracker" @default.
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• W2891599753 doi "https://doi.org/10.1145/3243734.3243735" @default.
• W2891599753 hasPublicationYear "2018" @default.
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