Embedded Obfuscated Barcodes for Identification of Genuine Additive Manufactured Parts

doi:10.21203/rs.3.rs-592866/v1

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Embedded Obfuscated Barcodes for Identification of Genuine Additive Manufactured Parts

https://doi.org/10.21203/rs.3.rs-592866/v1

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Additive manufacturing (AM) has been adopted for manufacturing complex shaped highly customized components for aerospace, automotive, and medical fields, where intellectual property protection and counterfeit detection are major concerns. New technologies such as Blockchain have been promising in supply chain authentication. However, AM due to layer-by-layer manufacturing process provides opportunities of embedding information inside the part during manufacturing, which has been explored recently to embed identification codes inside the parts. The present work studies the possibility of printing a barcode inside the additively manufactured part and develops a scheme to obfuscate the code design to read differently from different directions to enhance the security and protect the intellectual property. The embedded three-dimensional codes are scanned using a micro-CT scan. This scheme of embedded obfuscated codes proves to be a highly customizable and efficient process while securing product design files.

Biotechnology and Bioengineering

additive manufacturing

product security

barcodes

obfuscated codes

3D printing

Additive manufacturing (AM) has evolved as one of the promising manufacturing technologies in aerospace in medical sectors [1–3]. However, security of intellectual property (IP) and identification of counterfeit and unauthorized products have always been an issue in aerospace and medical sectors [4–6]. Cloud-based platforms have enabled sharing and collaboration for development of product designs; however, security of information has been a concern for such systems due to increased attack surface [7]. The attack taxonomy has been studied in the available literature and shows several possible attack vectors in the AM field [8]. Since AM is currently used for development and production of highly valued parts such as aircraft and spacecraft components and patient specific medical device parts, security concerns are amplified for this field [9–12]. The additively manufactured products are subjected to cyberattacks, counterfeiting or other illegal activities, causing huge financial loss and safety concerns [10, 13–17]. Currently, there is very limited discussion on the effective solutions to secure AM and its products. In the following Sect. 1.1, an overview of some of the anti-counterfeiting methods is presented along with the possible implementation of these methods in AM and its products. It is evident that the conventional security labels are highly subjected to removal-reapplication attacks, which will result in severe losses. Our scheme of embedding “security labels” inside the product can reduce the risk of security breach. Furthermore, we also propose a novel security strategy that is rooted in the design files to prevent counterfeiting production by efficiently distinguishing the fake products from genuine ones [18].

1.1 Overview of current product authentication tools

Authentication technologies and security tools are essential to all genuine products and their legitimate IP owners [19]. Anti-tamper devices, package and box seal, package sealing tapes are available for tamper resistance, but once exposed, the product identity can be still stolen and reproduced for counterfeits. Property marking is also made on the surface where products can be marked with security markers and stamping products [20, 21]. These markers can be in fluorescence but transparent and only visible under an UV light. However, this technique may be limited to protect high-value components with extremely small sizes such as a microchip due to writing difficulty. In addition, traces of these UV markings may be seen with naked eyes if not performed properly and subsequently removed by attackers. Other methods like holographic label printing anti-counterfeiting approach enabled by laser holographic technology are also used to prove product authenticity [20, 22]. ID card, passport, document laminates can be made using holographic technology with multi-color fluorescing inks, optically variable ink (OVIs) and liquid crystal solutions to create unique identifiable features [20, 22].

Credit cards and banknotes are designed to have holographic security labels on them which change colors as they are tilted [20, 23]. However, these labels are still subjected to duplication, reproduction or removal by attackers. Product serial numbers on a sticker label can be placed externally on the product and help to distinguish a genuine product from a counterfeit one but they can be scratched off to prevent product authentication or other logistic management [24]. For example, barcode or QR code labels are attached on the outer surface of consumer products so that they can be identified with a code scanner. This scanning system is favored by many businesses for high efficiency, productivity, and relatively low cost [24, 25]. The small barcode can encode sufficient amounts of information in a visual pattern. However, the tracking label can be damaged and lose its functionality. In addition, the radio-frequency identification (RFID) tags, with or without an electronic chip, have been widely used in many applications including warehouse logistics, product tracking in a supply chain, passports, and banknotes [23, 26]. In many applications like identity cards, passports or credit cards, RFID tags with integrated circuits (ICs) are used to prevent data theft and control access [26, 27]. An RFID tag or chip is more resistant to wearing damage but is still subjected to be removed or disabled by attackers similar to other product authentication labels.

1.2 Proposed AM product security approach

All the cybersecurity strategies can help to keep the product safe from counterfeiting, but once they are breached, IP can be stolen, and counterfeits can be produced. Therefore, we propose a security approach that protects the product at the design level, where parameters including printer capabilities, layer resolution, scanning resolution are taken into consideration. The aforementioned authentication tools and techniques can be subjected to damage at different levels. When applying these tools in AM and its products, surface labeling such as security marking or label attachments are highly vulnerable to the removal-reapplication attacks. Security labeling such as laser engraving tools can reduce the risks of removal-reapplication attacks to some extent, but also make the security features visible and subject to counterfeiting using 3D scanning reverse engineering. Therefore, in this work we study the possibility of embedding security and authentication codes inside the component that is intended for 3D printing at the product design level. Widely used barcodes are taken as an example in this study for the possibility of embedding them in product design. Such embedded codes would not be visible from outside and cannot be tempered.

Only by imaging techniques such as computed tomography (CT) scanning, the embedded features can be visualized and confirmed for authenticity. In this work, we have provided an extensive description for the CAD development with embedded features, the scanning and reading procedure, and further improved complexity on the embedded features. The design strategies, as discussed in previous studies [15, 28–31] were utilized to demonstrate the enhancement of product security by modifying the embedded features such that a unique set of processing parameters are required to produce parts with the correct embedded codes.

A barcode image representing the four letters “CMML” (that stands for “Composite Materials and Mechanics Lab”) is selected and imported into a 3D modelling software SolidWorks 2019 to construct a 3D CAD model of a cuboid with embedded barcode, which is then used for AM.

2.1 Embedded barcode models

2.1.1 One-layer barcode

One-dimensional zebra-striped barcodes are typically used in the retail industry for commercial products [32]. These 1D barcodes encode data only horizontally using black bars on a white background, which are sufficient enough for storing information such as numbers or short tags. For a string field with more than 25 characters, however, they are insufficient, let alone a text area field that has a 30,000 characters’ limit or URLs [32]. Despite their limited information storage capability, one dimensional barcodes are still widely used for high feasibility of creating and reading [33].

Code 128 is one of the most widely used 1D barcodes in shipping and packaging industries as a product identification code. Therefore, a code 128 is generated for the string character “CMML” using an online conversion tool as shown in Fig. 1(a), which contains machine readable information (in black strips) and human-readable text (in letters underneath) [33]. A 3D CAD model as shown in Fig. 1(b) is created in SolidWorks 2019 by first importing the barcode image in Fig. 1(a) and then using the “Sketch” and “Extruded Cut” functions to define contour, locations, and dimensions. The complete 1D barcode is embedded within a solid prism at the same depth and 3D printed using VeroClear transparent photopolymer for visualization of internal features as shown in Fig. 2. When imported in a Slicer program, the STL model is scaled down and printed in different sizes using the Stratasys Objet30 Pro resin 3D printer to evaluate possible miniaturization of using such codes. As depicted in Fig. 2, a part embedded with a 1D barcode can be 3D printed as small as 10 × 6 × 3 mm³ in length × width × thickness and still have a good visibility of the code to the naked eye. Smaller codes can be generated for reading through imaging methods.

2.1.2 Mechanical Testing on one-layer barcode

Parts with embedded codes are evaluated for their mechanical properties and structural integrity. It is expected that under the optimal design, with the security feature size minimized and properly positioned inside the part, the parts’ original functionality will not be compromised.

The standard tensile bar specimen geometry with embedded barcode feature is developed as shown in Fig. 3(a), where the same barcode pattern in Fig. 1 is used here. The volume of “Extruded Cut” barcode is 7.85 mm³ as compared to 15739.09 mm³ for the entire solid tensile bar, which gives a volumetric ratio of 0.0499% between barcode and tensile bar as in the CAD program. The tensile bar files are used for 3D printing using the Stratasys Objet30 Pro resin 3D printer and VeroClear photopolymer model material with high printing resolution down to 16-microns layer thickness. Meanwhile a set of standard tensile bars without any embedded codes are also printed using the same method to determine the baseline properties. The 3D printed tensile bar with embedded barcode is shown in Fig. 3(b), where the embedded barcode can be seen clearly from the front view. After visually validating the existing embedded barcodes, which are printed with support material (Stratasys SUP706) rather than the model material, standard tensile test is performed on 5 tensile specimens. Three tensile bars without embedded codes are also tested for reference (fewer than 5 specimens were tested due to high consistency; deviation is less than 1%).

The processed tensile test results are plotted in Fig. 4 with representative data from both categories, showing a close match between the stress-strain curves. The tensile properties are calculated and summarized in Table 1, where embedded code specimens show on average only ~ 0.35% lower tensile strength and ~ 0.39% lower modulus as compared to the reference specimens without embedded code. Therefore, it can be safely concluded that an embedded tracking code such as the one used in Fig. 3 would not significantly affect the part’s tensile properties, and hence can be a promising scheme to secure the product while preserving its strength and functionality.

Table 1

Tensile properties of both standard tensile specimens with and without embedded barcode.
Tensile Properties	Embedded Code	No Code (reference)
Ultimate Stress (MPa)	62.23 ± 0.91	62.45 ± 0.69
Modulus (GPa)	2.56 ± 0.14	2.57 ± 0.03

2.1.3 Multi-layer barcode

The same barcode representing “CMML” as in Fig. 1(a) is used to create the multi-layer barcode CAD model in SolidWorks 2015 as shown in Fig. 5. Similarly, the barcode image was first imported in SolidWorks and a total of 22 rectangular prisms were generated using the “Sketch” and “Extruded Cut” functions to define contour, locations, and dimensions. These 22 prisms represent the barcode pattern and are embedded at 22 different planes with distances equal to the white spacing between each black stripe of the barcode, inside a larger rectangular prism that is 56 × 56 × 40 mm³ in length × width × thickness. The 22 rectangular prisms are 30 mm in length with their square sides equal to 0.6 × 0.6 mm², 1.2 × 1.2 mm², or 1.8 × 1.8 mm², depending on the corresponding barcode stripe dimensions.

With careful placement, the top and right-side views can display the exact same barcode using the multiple layers embedding scheme as depicted in Fig. 5. Distances between each stripe and their widths are used to reconstruct the same barcode pattern on the side. By changing the thickness of each stripe, the side pattern can be dramatically different, leading to different barcode reading, or simply a false barcode. With the distributed layers of codes, it not only obfuscates the appearance of the 3D barcode, but also reduces the stress concentration as compared to the one-layer barcode model.

Once exported as STL file (coarse resolution), the model is sent to the Stratasys J750 3D printer and 3D printed using the multi-material 3D printing method (PolyJet), where the barcode volume is printed in red using VeroMagenta photopolymer, and outside enclosure cuboid is printed using VeroClear photopolymer for transparency as shown in Fig. 5.

2.2 Embedded obfuscating barcode models

The embedded tracking code can serve as a unique product signature by distinguishing itself from counterfeiting products that do not have any embedded tracking codes. However, when the entire design files are stolen, it is likely that expert attackers can use these design files to illegally reproduce parts with comparable quality and the same tracking code information. Therefore, we have modified the design of these embedded features such that they can be only printed correctly under a specific set of processing parameters such as printing orientation. In this case, despite being stolen, attackers will need to invest significant resources to determine the best combination of processing parameters to produce parts with high quality and the sane tracking codes, which can effectively distinguish counterfeits from the genuine products and protect the original rightful IP owner.

2.2.1 Obfuscating one-layer barcode

The embedded barcode feature can be modified with other 3D modelling features such as the surface feature to secure the original product. Here a CAD modeling scheme is developed such that the embedded barcode can only be 3D printed under a specific set of processing parameters (individual feature size, resolution of STL file and direction of slicing), while other attempts will not generate parts with the embedded barcode for an authentication process. In this way, attackers or other unauthorized users cannot reproduce the part with the embedded tracking code easily without knowing the processing parameters, which results in failure at passing the authentication steps.

The original CAD model for the barcode model is shown in Fig. 1(b), where the barcode stripes are extruded inside a solid prism. This model is modified such that the barcode stripes are applied with the “Extruded Surface” function inside the solid prism as shown in Fig. 6, so that it becomes an obfuscating embedded barcode model. Each barcode stripe is represented with an open surface in the same rectangular shape as the stripe. When these barcode stripes are performed with the “Extruded Surface” instead of the “Extruded Cut” function, the model shows orientation-dependent slicing results.

In the original CAD model, dimensions for the solid prism are 12 × 8 × 4 mm³, where the minimum width of the bar stripe is 0.13 mm. However, depending on the printer resolution and capability, a scale factor should be applied such that the minimum width of barcode stripe is a multiple of the printer layer thickness. The modified CAD model is translated to a standard tessellated file format STL and saved in coarse STL resolution, which is then imported to a slicer CatalystEX for FDM 3D printing. The minimum layer thickness 0.178 mm is chosen for 3D printing using this printer, therefore, the minimum width of stripe is scaled up to 0.178 mm with a scale factor of 1.37 applied to original CAD model dimensions, to ensure that it can be printed. The scaled model is sliced under default orientations and three other manually adjusted orientations, which are 90° rotations about x-, y-, and z-axis respectively. For this modified barcode model, auto-optimized orientation option is not available due to missing facets or reversed normal. Out of the four slicing orientations, it is observed that only the manually adjusted 90° rotation about x-axis orientation generates a toolpath for barcode, while other orientations slicing does not generate any barcode toolpath as shown in Fig. 7. It can be further indicated by the geometry of CAD model and slicing results that only when the extruded surfaces are normal to the slicing direction, the barcode extruded surface features can be recognized, and toolpath can be generated. However, when the smallest stripe width is 0.178 mm (scale factor of 1.37) the barcode pattern is not generated correctly as shown in Fig. 7(d) as opposed to Fig. 6(d). Therefore, the scale factor is further increased to 2.74 and 4.1 such that the smallest barcode stripe width is 0.356 mm and 0.534 mm, which are twice and thrice of the printer layer thickness, respectively.

It can be observed from the slicing results that toolpath of the barcode pattern is generated for both scaled model (2.74 and 4.1 scale factors) when placed under manually adjusted 90° rotation about x-axis orientation, however, the larger model with 4.1 scale factor has shown more precise barcode pattern toolpath than other models as shown in Fig. 8. Likewise, under the default orientation, all models (scale factor of 1.37, 2.74, and 4.1) generate toolpath only for the prism without any barcode stripes. These results have shown a close relationship between machine capability and design freedom. While AM allows a high degree of freeform fabrication, careful investigation needs to be implemented to achieve the best manufacturing outcomes. When the original design had a minimum stripe width below the printer resolution (0.178 mm), the security feature was not able to be implemented correctly. Under both XY and XZ orientations, the barcode stripes are printed with support materials in a wrong pattern. No difference can be observed when changing the slicing orientation with respect to the model. The slicing results are validated by the FDM printed parts as shown in Fig. 8, where support material is deposited for larger width barcode stripes and less for smaller widths.

From this experiment, it can be observed that when extra surfaces/planar surfaces are introduced, the STL tessellation file shows two surfaces, unlike the four extruded surfaces as originally in CAD model. When additional extruded surfaces (unclosed) are introduced in the solid prism, the solid prism shows “missing facets or reversed normal” error message in the Slicer when attempting to auto-optimize its orientation. Moreover, under the default orientation, the solid prism model is printed as one solid part without any support material deposited inside. However, when manual orientation to XY (90° rotation to x-axis from default), the embedded column of surface features is printed with the support material in the pattern of correct barcode design, and under all other 90° rotation, the model is printed as one solid part. But this phenomenon may or may not occur under other 3D printing techniques and slicing algorithms. In summary, by introducing four surfaces (in the shape of rectangular tube) with determined dimensions, a column of support materials can be printed without any dependence on the slicing orientation. Authentic parts will be printed by authorized users where support materials are deposited showing the barcode pattern for tracking and authentication process.

A micro-CT scanning and reconstruction by the Micro-CT system is performed on the FDM 3D printed modified barcode part as in Fig. 8(a) to validate previous discussion on the reading techniques. The printed prism, Fig. 8(b), is subjected to micro-CT scan and then cut to physically verify the presence of the code Fig. 8(c). When exposed to x-ray radiation as in Fig. 8(c), color indication shows the barcode stripes as printed with a different material than the prism model material. This can also quickly help in validating different printing results for the modified barcode model with security features under different orientations. Further, a 3D model can be reconstructed from the computed tomography scanned cross-section images. This step is necessary because the scanning orientation might not be sufficient to visualize the barcode pattern based on the assumption that this kind of tracking code can be embedded with 360° degree of freedom. The reconstructed model can be viewed at any angle and any cross-section to visualize the barcode pattern as in Fig. 8(c), which shows relatively good barcode pattern and contrast. With improved printer capability and resolution, dimensional accuracy can be increased, and the tracking code can be read faster.

2.2.2 Obfuscating multi-layer barcode

By combining the findings described earlier in the sections on multi-layer barcode and obfuscating one-layer bar code, the multi-layer barcode model as shown in Fig. 5 is enhanced with obfuscation security feature so that only under certain conditions will the correct barcode be printed, and only a certain viewing orientation can read the code correctly. The “Extruded Surface” function is performed on the barcode instead of “Extruded Cut” function. The “Extruded Surface” barcode is 30 mm in length with square sides that are either 0.6 × 0.6 mm², 1.2 × 1.2 mm², or 1.8 × 1.8 mm², all embedded inside a cuboid enclosure that is 56 × 40 × 56 mm³ in length × width × height as shown in Fig. 9. The STL model is exported in coarse STL resolution, which is then imported into the slicer CatalystEX and sliced under different orientations as shown in Fig. 10. Only under the 90° rotation about x-axis will the barcode be printed correctly while other orientations cannot print the barcode at all. The STL model is then scaled down (scale factor 0.4) to a smaller size compatible for micro-CT imaging and sliced after rotations (x-90° and z-90°) as in Fig. 10(b) and (d) in CatalystEX (Stratasys, USA), and then sent the Stratasys Dimension Elite FDM 3D printer for 3D printing in ABSplus-P430 (Stratasys, USA) filament material. The two 3D printed cuboids have a dimension of 22.4 × 16 × 22.4 mm³ in length × width × height. The cuboid part that is sliced under 90° rotation about x-axis is subjected to micro-CT scan and reconstructed in NRecon Reconstruction Software to generate a 3D model of the scanned part. The reconstructed 3D model is opened in SolidWorks 2018 and displayed from side and isometric views as in Fig. 11 to validate that the x-90° rotation slicing orientation can properly generate the embedded barcode inside the 3D printed cuboid.

2.3 Reading techniques

The tracking codes embedded inside the solid model benefit from the freeform solid modelling stage of AM. In previous examples, we have developed CAD models with embedded tracking code and additively manufactured 3D objects from these CAD models in a transparent photosensitive polymer material to facilitate visualization and code pattern validation. However, such a scheme can be developed into any 3D solid model and produced with any materials, without the necessity of being transparent. Under the scenario of an opaque or translucent appearance model, direct code reading might not be feasible so an external facility for internal structure visualization needs to be employed. Examples of such non-destructive reading techniques include ultrasonic imaging and x-ray computed tomography (CT). Here we demonstrate the feasibility of using a micro-CT machine to acquire internal information of a 3D printed product with embedded tracking code. During the acquisition, a series of cross-sectional slices will be generated for the object and used for 3D model reconstruction. Once the internal pattern is reconstructed using the CT-scan machine, an efficient image processing scheme can be adopted to validate product authenticity.

From the CAD models and printed objects, it can be observed that currently, AM technologies are capable of manufacturing tracking codes with similar geometries at high resolution and miniaturized size. Therefore, in the processing of this reconstructed image, it is promising to apply pre-determined geometry such as rectangular or squares so as to discriminate signal noises and only acquire the useful information for image analysis and code authentication. With this, our scheme of a robust and highly efficient authentication process can be realized and compatible with a broad selection of products.

The process of designing, printing, and reading an embedded tracking code is successfully demonstrated in this article. The 1D barcode example is used for illustration, but more complex design or a multi-layered code can also be implemented following the similar protocol. Compared to the conventional security labels that are highly subjected to removal-reapplication attacks, our scheme of embedding “security labels” inside the product can reduce the risk of security breach. Combined with the additional obfuscation design, the embedded feature complexity and security is increased to further distinguish the genuine product from counterfeits. Unauthorized users without access to the key process parameters will eventually produce counterfeits without the embedded security feature that will fail the authentication process.

FUNDING/ACKNOWLEDGMENTS

This work is supported by the National Science Foundation grant DGE-1931724 from the Secure and Trustworthy Cyberspace program. Authors thank NYU Tandon Makerspace for the facilities and support provided for the experimental work. The views presented in this article are those of the authors, not of the funding agency.

Conflicts of interest/Competing interests:

The authors have no conflicts of interest to declare that are relevant to the content of this article.

Availability of data and material:

Data can be provided if requested.

Code availability:

Not applicable.

Ethics approval:

This article does not contain any studies with human participants or animals performed by any of the authors.

Consent to participate:

There are no human participants that are included in the study.

Consent for publication:

The authors have not included any data taken from other individuals.

Abdulhameed O, Al-Ahmari A, Ameen W, Mian SH (2019) Additive manufacturing: Challenges, trends, and applications. Advances in Mechanical Engineering 11(2):1687814018822880
Mohd Yusuf S, Cutler S, Gao N (2019) Review: The Impact of Metal Additive Manufacturing on the Aerospace Industry. Metals 9(12):1286
Longhitano GA, Nunes GB, Candido G, da Silva JVL (2021) The role of 3D printing during COVID-19 pandemic: a review. Progress in Additive Manufacturing 6(1):19–37
Zeltmann SE, Gupta N, Tsoutsos NG, Maniatakos M, Rajendran J, Karri R (2016) Manufacturing and Security Challenges in 3D Printing. JOM 68(7):1872–1881
Yampolskiy M, Andel T, McDonald J, Glisson W, Yasinsac A, Intellectual Property Protection in Additive Layer Manufacturing: Requirements for Secure Outsourcing (2014) 1–9
Padmanabhan A, Zhang J (2018) Cybersecurity risks and mitigation strategies in additive manufacturing. Progress in Additive Manufacturing 3(1):87–93
Sengupta S, Kaulgud V, Sharma VS. Cloud computing security–trends and research directions. in 2011 IEEE World Congress on Services. 2011
Mahesh P, Tiwari A, Jin C, Kumar PR, Reddy ALN, Bukkapatanam STS, Gupta N, Karri R, A Survey of Cybersecurity of Digital Manufacturing. Proceedings of the IEEE, 2020, 1–22
Yampolskiy M, Skjellum A, Kretzschmar M, Overfelt RA, Sloan KR, Yasinsac A (2016) Using 3D printers as weapons. Int J Crit Infrastruct Prot 14(Supplement C):58–71
Kurfess T, Cass WJ (2014) Rethinking Additive Manufacturing and Intellectual Property Protection. Research-Technology Management 57(5):35–42
Rengier F, Mehndiratta A, von Tengg-Kobligk H, Zechmann CM, Unterhinninghofen R, Kauczor H-U, Giesel FL, 3D printing based on imaging data: review of medical applications. International Journal of Computer Assisted Radiology and Surgery, 2010, 5(4), 335–341
Egan PF, Bauer I, Shea K, Ferguson SJ (2019) Mechanics of Three-Dimensional Printed Lattices for Biomedical Devices. J Mech Des 141(3):031703
Bridges SM, Keiser K, Sissom N, Graves SJ Cyber Security for Additive Manufacturing. in Proceedings of the 10th Annual Cyber and Information Security Research Conference. April 7–9, 2015 Oak Ridge, TN, USA: ACM
Sturm LD, Williams CB, Camelio JA, White J, Parker R, Cyber-physical vulnerabilities in additive manufacturing systems: A case study attack on the.STL file with human subjects. Journal of Manufacturing Systems, 2017, 44, Part 1, 154–164
Gupta N, Chen F, Shahin K, Design features to address security challenges in additive manufacturing, Manufacturing Techniques for Materials: Engineering and Engineered, T.S. Srivatsan, T.S. Sudarshan, and K. Manigandan, Editors. 2018, CRC Press: Taylor & Francis Group
Bayens C, Le T, Garcia L, Beyah R, Javanmard M, Zonouz S See no evil, hear no evil, feel no evil, print no evil? Malicious fill patterns detection in additive manufacturing. in 26th {USENIX} Security Symposium ({USENIX} Security 17) (2017) Vancouver, BC: {USENIX} Association
Chaduvula SC, Dachowicz A, Atallah MJ, Panchal JH (2018) Security in Cyber-Enabled Design and Manufacturing: A Survey. J Comput Inf Sci Eng 18(4):040802
Gupta N (2020) Embedded security elements for digital models used in additive manufacturing. Google Patents
Lehtonen M, Oertel N, Vogt H Features, identity, tracing, and cryptography in product authentication. in (2007) IEEE International Technology Management Conference (ICE). 2007. Sophia-Antipolis, France: IEEE
Shah RY, Prajapati PN, Agrawal Y (2010) Anticounterfeit packaging technologies. J Adv Pharm Tech Res 1(4):368
Li L (2013) Technology designed to combat fakes in the global supply chain. Bus Horiz 56(2):167–177
Craver S, Memon N, Yeo B, Yeung MM (1998) Resolving rightful ownerships with invisible watermarking techniques: limitations, attacks, and implications. IEEE J Sel Areas Commun 16(4):573–586
Juels A, Pappu R Squealing Euros: Privacy Protection in RFID-Enabled Banknotes. in International Conference on Financial Cryptography (2003) Berlin, Heidelberg: Springer Berlin Heidelberg
Qian J-P, Yang X-T, Wu X-M, Zhao L, Fan B-L, Xing B (2012) A traceability system incorporating 2D barcode and RFID technology for wheat flour mills. Comput Electron Agric 89:76–85
Mun IK, Kantrowitz AB, Carmel PW, Mason KP, Engels DW Active RFID System Augmented With 2D Barcode for Asset Management in a Hospital Setting. in (2007) IEEE International Conference on RFID. 2007. Grapevine, TX, USA: IEEE
Song B, Mitchell CJ. RFID authentication protocol for low-cost tags. in Proceedings of the first ACM conference on Wireless network security (2008) Alexandria, VA, USA: ACM
Lehtonen MO, Michahelles F, Fleisch E (2007) Trust and security in RFID-based product authentication systems. IEEE Syst J 1(2):129–144
Chen F, Mac G, Gupta N (2017) Security features embedded in computer aided design (CAD) solid models for additive manufacturing. Materials Design 128:182–194
Chen F, Yu JH, Gupta N, Obfuscation of embedded codes in additive manufactured components for product authentication. Advanced Engineering Materials, 2019
Gupta N, Chen F, Tsoutsos NG, Maniatakos M ObfusCADe: Obfuscating additive manufacturing CAD models against counterfeiting: Invited. in Proceedings of the 54th Annual Design Automation Conference (2017) 2017. Austin, TX, USA: ACM
Chen F, Luo Y, Tsoutsos NG, Maniatakos M, Shahin K, Gupta N (2018) Embedding tracking codes in additive manufactured parts for product authentication. Adv Eng Mater. doi:10.1002/adem.201800495
Peternikolow. 1D, 2D & 3D Barcodes (2012) [cited 2021 June 2]; Available from: http://www.mobiliodevelopment.com/1d-2d-3d-barcodes/
Peternikolow. Code39 and Code128 in a nutshell (2012) [cited 2021 June 2]; Available from: http://www.mobiliodevelopment.com/code39-and-code128-usage/

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Embedded Obfuscated Barcodes for Identification of Genuine Additive Manufactured Parts

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Abstract

Figures

1. Introduction

1.1 Overview of current product authentication tools

1.2 Proposed AM product security approach

2. Design And Process Development

2.1 Embedded barcode models

2.1.1 One-layer barcode

2.1.2 Mechanical Testing on one-layer barcode

2.1.3 Multi-layer barcode

2.2 Embedded obfuscating barcode models

2.2.1 Obfuscating one-layer barcode

2.2.2 Obfuscating multi-layer barcode

2.3 Reading techniques

3. Conclusions

Declarations

References

Supplementary Files

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