skip to main content
10.1145/3450267.3450545acmconferencesArticle/Chapter ViewAbstractPublication PagesiccpsConference Proceedingsconference-collections
research-article

Spatiotemporal G-code modeling for secure FDM-based 3D printing

Published: 19 May 2021 Publication History

Abstract

3D printing constructs physical objects by building and stacking layers according to the CAD (Computer-aided Design) information. Attackers target a printing object by manipulating the printing parameters such as nozzle movement and temperature. The existing research on secure 3D printing mostly focuses on nozzle-kinetics, while attacks on filament-kinetics and thermodynamics can also damage the printed object. The detection of these attacks mainly relies on creating master-profile and machine learning by printing every unique object in a protected environment. In the fourth industrial revolution, such an approach is not suitable due to mass-customization rather than bulk production. This paper presents Sophos, a framework to detect nozzle-kinetic, filament-kinetic and thermodynamic attacks on the fused deposition modeling (FDM)-based 3D printing process. Sophos design does not require any prior learning for every unique object. It can detect the attacks on the first print using spatiotemporal G-code modeling, aligning it with the Industry 4.0 vision. Sophos is scalable and supports modular upgrades to suit different printing requirements. Its design allows the detection threshold to be reduced conveniently to as low as the 3D printer's resolution, shifting the game to a more interesting study of attack patterns than attack magnitudes.

References

[1]
Ugur M. Dilberoglu, Bahar Gharehpapagh, Ulas Yaman, and Melik Dolen. The role of additive manufacturing in the era of industry 4.0. Procedia Manufacturing, 11: 545 -- 554, 2017. ISSN 2351-9789. URL http://www.sciencedirect.com/science/article/pii/S2351978917303529. 27th International Conference on Flexible Automation and Intelligent Manufacturing, FAIM2017, 27-30 June 2017, Modena, Italy.
[2]
Statistica. Statistica, worldwide most used 3d printing technologies, as of july 2018, 2020. URL https://www.statista.com/statistics/756690/worldwide-most-used-3d-printing-technologies.
[3]
Shahrain Mahmood, AJ Qureshi, Kheng Lim Goh, and Didier Talamona. Tensile strength of partially filled fff printed parts: experimental results. Rapid prototyping journal, 23(1):122--128, 2017. ISSN 1355-2546.
[4]
Steven Eric Zeltmann, Nikhil Gupta, Nektarios Georgios Tsoutsos, Michail Maniatakos, Jeyavijayan Rajendran, and Ramesh Karri. Manufacturing and security challenges in 3d printing. JOM, 68(7):1872--1881, Jul 2016. ISSN 1543-1851. URL https://doi.org/10.1007/s11837-016-1937-7.
[5]
Yang Gao, Borui Li, Wei Wang, Wenyao Xu, Chi Zhou, and Zhanpeng Jin. Watching and safeguarding your 3d printer: Online process monitoring against cyber-physical attacks. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2(3), September 2018. URL https://doi.org/10.1145/3264918.
[6]
Shouling Ding, Bin Zou, Peng Wang, and Hongjian Ding. Effects of nozzle temperature and building orientation on mechanical properties and microstructure of peek and pei printed by 3d-fdm. Polymer Testing, 78:105948, 2019. ISSN 0142-9418. URL http://www.sciencedirect.com/science/article/pii/S0142941819304994.
[7]
Martin Spoerk, Joamin Gonzalez-Gutierrez, Janak Sapkota, Stephan Schuschnigg, and Clemens Holzer. Effect of the printing bed temperature on the adhesion of parts produced by fused filament fabrication. Plastics, Rubber and Composites, 47(1):17--24, 2018. URL https://doi.org/10.1080/14658011.2017.1399531.
[8]
Mark Yampolskiy, Lena Schutzle, Uday Vaidya, and Alec Yasinsac. Security challenges of additive manufacturing with metals and alloys. In Mason Rice and Sujeet Shenoi, editors, Critical Infrastructure Protection IX, pages 169--183, Cham, 2015. Springer International Publishing. ISBN 978-3-319-26567-4.
[9]
Mark Yampolskiy, Wayne E. King, Jacob Gatlin, Sofia Belikovetsky, Adam Brown, Anthony Skjellum, and Yuval Elovici. Security of additive manufacturing: Attack taxonomy and survey. Additive Manufacturing, 21:431 -- 457, 2018. ISSN 2214-8604. URL http://www.sciencedirect.com/science/article/pii/S221486041730502X.
[10]
Samuel Bennett Moore, William Bradley Glisson, and Mark Yampolskiy. Implications of malicious 3d printer firmware. In Proceedings of Hawaii Int. Conf.Syst.Sci,2017, pages 1--10, 2017. URL http://hdl.handle.net/10125/41899.
[11]
Tian-Ming Wang, Jun-Tong Xi, and Ye Jin. A model research for prototype warp deformation in the fdm process. International Journal of Advanced Manufacturing Technology, 33:1087--1096, 08 2007.
[12]
S. R. Chhetri, A. Canedo, and M. A. Al Faruque. Kcad: Kinetic cyber-attack detection method for cyber-physical additive manufacturing systems. In 2016 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), pages 1--8, 2016.
[13]
S. Belikovetsky, Y. A. Solewicz, M. Yampolskiy, J. Toh, and Y. Elovici. Digital audio signature for 3d printing integrity. IEEE Transactions on Information Forensics and Security, 14(5):1127--1141, 2019.
[14]
Mingtao Wu, Heguang Zhou, Longwang Lin, Bruno Silva, Zhengyi Song, Jackie Cheung, and Young Moon. Detecting attacks in cybermanufacturing systems: Additive manufacturing example. MATEC Web of Conferences, 108:06005, 01 2017.
[15]
Christian Bayens, Tuan Le, Luis Garcia, Raheem Beyah, Mehdi Javanmard, and Saman Zonouz. 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), pages 1181--1198, Vancouver, BC, August 2017. USENIX Association. ISBN 978-1-931971-40-9. URL https://www.usenix.org/conference/usenixsecurity17/technical-sessions/presentation/bayens.
[16]
J. Gatlin, S. Belikovetsky, S. B. Moore, Y. Solewicz, Y. Elovici, and M. Yampolskiy. Detecting sabotage attacks in additive manufacturing using actuator power signatures. IEEE Access, 7:133421--133432, 2019.
[17]
S. Yu, A. V. Malawade, S. R. Chhetri, and M. A. Al Faruque. Sabotage attack detection for additive manufacturing systems. IEEE Access, 8:27218--27231, 2020.
[18]
Sofia Belikovetsky, Mark Yampolskiy, Jinghui Toh, Jacob Gatlin, and Yuval Elovici. dr0wned - cyber-physical attack with additive manufacturing. In 11th USENIX Workshop on Offensive Technologies (WOOT 17), Vancouver, BC, August 2017. USENIX Association. URL https://www.usenix.org/conference/woot17/workshop-program/presentation/belikovetsky.
[19]
Guanxiong Miao, Sheng-Jen Hsieh, J. Segura, and Jia-Chang Wang. Cyber-physical system for thermal stress prevention in 3d printing process. The International Journal of Advanced Manufacturing Technology, 100, 01 2019.
[20]
Young Choi, Cheol-Min Kim, Hwan-Seock Jeong, and Jeong-Ho Youn. Influence of bed temperature on heat shrinkage shape error in fdm additive manufacturing of the abs-engineering plastic. World Journal of Engineering and Technology, 04:186--192, 01 2016.
[21]
Nahal Aliheidari, Rajasekhar Tripuraneni, Cameron Hohimer, Josef Christ, Amir Ameli, and Siva Nadimpalli. The impact of nozzle and bed temperatures on the fracture resistance of FDM printed materials. In Nakhiah C. Goulbourne, editor, Behavior and Mechanics of Multifunctional Materials and Composites 2017, volume 10165, pages 222 -- 230. International Society for Optics and Photonics, SPIE, 2017. URL https://doi.org/10.1117/12.2260105.
[22]
Q. Do, B. Martini, and K. R. Choo. A data exfiltration and remote exploitation attack on consumer 3d printers. IEEE Transactions on Information Forensics and Security, 11(10):2174--2186, 2016.
[23]
Logan D. Sturm, Christopher B. Williams, Jamie A. Camelio, Jules White, and Robert Parker. Cyber-physical vulnerabilities in additive manufacturing systems: A case study attack on the .stl file with human subjects. Journal of Manufacturing Systems, 44:154 -- 164, 2017. ISSN 0278-6125. URL http://www.sciencedirect.com/science/article/pii/S0278612517300961.

Cited By

View all
  • (2024)Investigating Digital Forensic Artifacts Generated from 3D Printing Slicing Software: Windows and Linux AnalysisElectronics10.3390/electronics1314286413:14(2864)Online publication date: 20-Jul-2024
  • (2024)Editors’ Choice—Review—Sensor-Based and Computational Methods for Error Detection and Correction in 3D PrintingECS Sensors Plus10.1149/2754-2726/ad7a883:3(030602)Online publication date: 26-Sep-2024
  • (2024)Sabotaging Material Extrusion-Based 3D Printed Parts through Low-Magnitude Kinetic Manipulation AttacksACM Transactions on Cyber-Physical Systems10.1145/37047359:1(1-26)Online publication date: 18-Nov-2024
  • Show More Cited By

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
ICCPS '21: Proceedings of the ACM/IEEE 12th International Conference on Cyber-Physical Systems
May 2021
242 pages
ISBN:9781450383530
DOI:10.1145/3450267
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

In-Cooperation

  • IEEE-CS\TCRT: TC on Real-Time Systems

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 May 2021

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. 3D printing
  2. filament-kinetic attacks
  3. thermodynamic attacks

Qualifiers

  • Research-article

Conference

ICCPS '21
Sponsor:

Acceptance Rates

Overall Acceptance Rate 25 of 91 submissions, 27%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)81
  • Downloads (Last 6 weeks)7
Reflects downloads up to 16 Feb 2025

Other Metrics

Citations

Cited By

View all
  • (2024)Investigating Digital Forensic Artifacts Generated from 3D Printing Slicing Software: Windows and Linux AnalysisElectronics10.3390/electronics1314286413:14(2864)Online publication date: 20-Jul-2024
  • (2024)Editors’ Choice—Review—Sensor-Based and Computational Methods for Error Detection and Correction in 3D PrintingECS Sensors Plus10.1149/2754-2726/ad7a883:3(030602)Online publication date: 26-Sep-2024
  • (2024)Sabotaging Material Extrusion-Based 3D Printed Parts through Low-Magnitude Kinetic Manipulation AttacksACM Transactions on Cyber-Physical Systems10.1145/37047359:1(1-26)Online publication date: 18-Nov-2024
  • (2024)PowerGuard: Using Power Side-Channel Signals to Secure Motion Controllers in ICSIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.345136219(8275-8290)Online publication date: 2024
  • (2023)Data Security in Additive ManufacturingAdditive Manufacturing Design and Applications10.31399/asm.hb.v24A.a0006962(203-209)Online publication date: 30-Jun-2023
  • (2023)Gadgets of Gadgets in Industrial Control Systems: Return Oriented Programming Attacks on PLCs2023 IEEE International Symposium on Hardware Oriented Security and Trust (HOST)10.1109/HOST55118.2023.10132957(215-226)Online publication date: 1-May-2023
  • (2023)SOK: Side Channel Monitoring for Additive Manufacturing - Bridging Cybersecurity and Quality Assurance Communities2023 IEEE 8th European Symposium on Security and Privacy (EuroS&P)10.1109/EuroSP57164.2023.00071(1160-1178)Online publication date: Jul-2023
  • (2022)LOW-MAGNITUDE INFILL STRUCTURE MANIPULATION ATTACKS ON FUSED FILAMENT FABRICATION 3D PRINTERSCritical Infrastructure Protection XVI10.1007/978-3-031-20137-0_8(205-232)Online publication date: 30-Nov-2022
  • (2022)DETECTING PART ANOMALIES INDUCED BY CYBER ATTACKS ON A POWDER BED FUSION ADDITIVE MANUFACTURING SYSTEMCritical Infrastructure Protection XVI10.1007/978-3-031-20137-0_7(175-203)Online publication date: 30-Nov-2022
  • (2022)Attacking the IEC 61131 Logic Engine in Programmable Logic ControllersCritical Infrastructure Protection XV10.1007/978-3-030-93511-5_4(73-95)Online publication date: 4-Jan-2022
  • Show More Cited By

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media