Artificial Intelligence’s Role in Trusted National Security Supply Chains Published May 27, 2022 By LtCol Gabe S. Arrington, USAF and CDR Andrew Adams, U.S. Navy Wild Blue Yonder -- U.S. economic prosperity and national security is at risk due to a dependency on the resiliency, diversity, and security of global supply chains. The U.S. government established Executive Orders, Acts of Congress, and Federal Task Forces that champion the dire need for supply chain reform to protect all aspects of national power.1 The American public has felt the impact of consumer product availability and have witnessed how unprecedented world events can impact their personal comfort. A less evident aspect of concern is the inherent risk to national security when the totality of Defense Industrial Base (DIB) supply lines is not understood. For top-level policies to be effective in addressing this national security concern, they must be backed with pragmatic Artificial Intelligence (AI) capabilities to verify trusted suppliers. Major technology companies, including IBM, have introduced supply chain AI workflow solutions that support lower costs, regulatory compliance, and product tracking.2 This technology also has the potential to “self-heal” during the massive shock of an unforeseen pandemic, natural disaster, or cyber-attack.3 It is critical that AI adoption also evolve in the name of national security resilience to identify multi-tier trust of the companies involved in the process. The current visible paradigm of supply chain management is oriented on point-to-point transactions between top-level suppliers and buyers. The vulnerable sub-tier, or upstream, supply chain network is more opaque, largely due to organizational hesitancy to share information that can compromise competitive position, reveal compliance posture, or highlight security concerns. The illusive picture of full-tier supply sources available to regulators and national security agencies can be exposed through machine learning (ML) platforms produced by emerging AI companies like Altana Technologies.4 Altana’s mission is to find truth in the global supply chain by pioneering a new technology, federated learning, to bring ML computation directly to siloed data that can never be pooled directly due to concerns over privacy, intellectual property, and sovereignty. The result is a living, intelligent model of global supply chain suppliers on top of a federated network of protected data.5 The U.S. space industry is a prime case study where a lack of supply chain transparency is a threat to national security. This industry, that frequently has overlapping civilian and military priorities, is estimated to have a market value over $10 billion by 2030. As innovation has driven the launch cost per kilogram from $20,000 to an estimated $500, 10,000 global companies are now entered into the booming market, only 52 percent of which are U.S. based.6 As this interconnected sector grows, so do the vulnerabilities in a vital U.S. supply chain that lacks a common operating picture. The State of the Space Industrial Base 2021 Report highlights that the space sector is tactically strong but strategically fragile based on a dependency on commercial contracts and fragile domestic supply lines.7 Altana’s platform reveals that U.S. space supply chains have significant exposure to non-traditional players that may require more sub-tier analysis to prove trust. For example, ViaSat, a leader in high-speed satellite broadband and secure networking systems for both the military and commercial markets have several critical relationships with Taiwanese companies.8 Additionally, multinational manufacturer GKN, is a second-tier space supplier that uses Mexican-based plants.9 More concerning than a current lack of vetting of new international suppliers is that Altana also identified several top-tier source material suppliers that are subject to U.S. sanctions or have links to Russian and Chinese military-industrial complexes. For example, NPK Precision Instrumentation Systems, a Russian aerospace systems manufacturer that supplies Russia’s space-based early warning system and is sanctioned by the U.S., appears to have supplied optical lasers to a leading U.K.-based small satellite company, likely for use with the European Galileo satellite constellation.10 Russian involvement in the Galileo constellation has become routine, yet not commonly known.11 Sanctions aside, current mounting tensions in Ukraine illustrate the increased risk of unplanned disruptions to critical space supply chains if the industry is unwittingly trusting Russian military-industrial sources. Supply chains must cross borders for U.S. innovation and capabilities to thrive in critical DIB sectors like the space. While there are various efforts underway to identify inherent risk and protect U.S. national security through supply chain resiliency, the U.S. must also bridge the gap to implementation with AI-enabled trusted supplier transparency. The fast paced, critically important DIB supply process requires maximum visibility for decision makers when awarding contracts and conducting operational planning to ensure national security is not sacrificed when promoting economic progress. Lt Col Gabe S. Arrington Lieutenant Colonel Gabe S. Arrington is a National Defense Fellow at the Center for a New American Security in Washington, D.C and Seminar XXI fellow at the Massachusetts Institute of Technology. Prior to his current assignment he was the executive officer to the vice chairman of the Joint Chiefs of Staff. CDR Andrew Adams CDR Andrew Adams, U.S. Navy, is a Federal Executive Fellow at the Center for a New American Security in Washington, DC. His previous assignments include U.S. Fleet Cyber Command/U.S. Tenth Fleet and the Cyber National Mission Force. NOTES 1. “The Federal Register,” Federal Register :: Request Access, accessed May 25, 2022, https://www.federalregister.gov/documents/2021/03/01/2021-04280/americas-supply-chains; “Rules Committee Print 117–31 - Docs.house.gov,” accessed May 25, 2022, https://docs.house.gov/billsthisweek/20220131/BILLS-117HR4521RH-RCP117-31.pdf; “Information and Communications Technology Supply Chain Risk Management,” Cybersecurity and Infrastructure Security Agency CISA, accessed May 25, 2022, https://www.cisa.gov/supply-chain. 2. “AI-Based Supply Chains: Using Intelligent Automation to Build Resiliency - IBM Supply Chain,” IBM Supply Chain Blog, September 20, 2021, https://www.ibm.com/blogs/supply-chain/ai-based-supply-chains-using-intelligent-automation-to-build-resiliency/. 3. 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