Internet of nuclear things: Managing the proliferation risks of 3-D printing technology

ABSTRACT

Over the next decade, the spread and maturation of additive manufacturing could challenge major control mechanisms for inhibiting nuclear proliferation. At the same time, the cyber-physical nature of this production technology creates the potential for the emergence of an Internet of Nuclear Things, which could be harnessed to increase the information visibility of dual-use activities in civil nuclear programs. This new capability could offer unique opportunities to mitigate proliferation risks and augment traditional methods of regulating and monitoring sensitive nuclear technologies. But barriers stand in the way of leveraging an Internet of Nuclear Things – notably, political issues related to information access and integrity. As additive manufacturing technology matures, government and industry stakeholders should adopt a strategic approach toward an evolving Internet of Nuclear Things – an approach that would include principles to encourage transparency within the Internet of Nuclear Things and ensure the integrity of the information it produces.

KEYWORDS:

• Additive manufacturing
• civil nuclear industry
• internet of nuclear things
• nuclear proliferation
• nonproliferation community
• 3-D printing

Acknowledgment

The authors are grateful for outstanding feedback on an earlier version of this article from participants at a December 2017 workshop dinner hosted by the Stanley Foundation in Washington, DC, as well as from Kevin Cuddy, Toby Dalton, Danielle Jablanski, Eli Levite, Ben Loehrke, and Tim Maurer.

Disclosure statement

No potential conflict of interest was reported by the authors.

Funding

A generous grant from the MacArthur Foundation funded Tristan Volpe’s research at the Carnegie Endowment on 3-D printing and the future of proliferation.

Notes

1. See, for example, Office of Nuclear Energy (2016); General Electric (2016); Karoutas (2017).

2. For a good technical overview, see Bandyopadhyay and Bose (2015).

3. The general additive manufacturing process begins with the design of a “digital build file” or a virtual blueprint of whatever product is to be fabricated. This design file is then converted into a standard format used by 3-D printers (often an .STL file), which consists of a string of coordinates identifying the dimensions of the design, as well as a toolpath file of automated commands to guide the robotic printer components. Finally, these commands are sent to the printer itself, which fabricates the final product. See Sturm et al. (2017); DeSmit et al. (2016).

4. On how additive manufacturing might shape the future of conventional defense production and operations, see Horowitz (2014).

5. See Paulsen (2015). For an introductory discussion on the Confidentiality Integrity and Assurance (CIA) analytic framework, see Singer and Friedman (2014).

6. We do not focus on the third type of attack on the availability of data, whereby an intruder targets a critical online service used by the manufacturer to coordinate activities, such as overwhelming it with requests in a denial-of-service attack. See “Cybersecurity for Manufacturing Networks” (2017).

7. The risk of such an attack is not remote, as efforts are under way to develop quality control methods based on incorporating in situ sensors into machines and leveraging high-performance computing. See King et al. (2015).

8. On proliferation pathways and strategies, see Einhorn (2006); Narang (2017). On how countries have integrated dual-use nuclear technology to achieve foreign policy objectives, see Volpe (2017a).

9. For an overview of how this logic might impact non-nuclear manufacturing and supply chains, see Fuchs (2014); Hammes (2015).

10. For a similar argument in the historical context of US nonproliferation policy, see Volpe (2016).

11. This scenario may be closer to reality than is often assumed, as research organizations are already experimenting with methods to 3-D print different types of nuclear reactor fuel. See “Idaho National Lab’s ‘AMAFT’ Makes 3-D Printed Nuclear Fuel” (2017).

12. Nuclear energy programs that invest in additive manufacturing technology would thereby run the risk of creating a moderate security dilemma as other nations responded to this potential threat of proliferation. See Beardsley and Asal (2013); Volpe (2017b).

13. We use several established proliferation assessment methodologies to construct these conceptual containers. See for example, Einhorn (2006); Crawford (2011); Tucker (2012); Bowen, Dover, and Goodman (2014). In particular, this section draws heavily on the Carnegie Endowment’s Nuclear Firewall methodology; see Dalton et al. (2017).

14. To offer one example, blockchain technology is being explored as a solution for supply chain security in numerous industries. See Hsieh and Ravich (2017).

15. This idea builds on recent research by Nicholas L. Miller of Dartmouth College, who finds that nuclear energy programs often generate political obstacles to developing nuclear weapons, such as attracting greater scrutiny of intentions and attention from intelligence agencies; see Miller (2017).

16. For further discussion of the application of blockchain technology to supply chain security, see Hsieh and Ravich (2017); Trouton, Vitale, and Killmeyer (2016).

Additional information

Funding

A generous grant from the MacArthur Foundation funded Tristan Volpe’s research at the Carnegie Endowment on 3-D printing and the future of proliferation.

Notes on contributors

Wyatt Hoffman

Wyatt Hoffman is a research analyst with the Cyber Policy Initiative at the Carnegie Endowment for International Peace.

Tristan A. Volpe

Tristan A. Volpe is an assistant professor in the Defense Analysis Department at the Naval Postgraduate School and a nonresident fellow at the Carnegie Endowment for International Peace.