mlsanityData to 14 Oct 2026

AI threats to national security can be countered through an incident regime

arXiv 2503.19887 ↗First posted 25 Mar 2025cs.CY cs.AIcited by 1

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Abstract (arXiv)

Recent progress in AI capabilities has heightened concerns that AI systems could pose a threat to national security, for example, by making it easier for malicious actors to perform cyberattacks on critical national infrastructure, or through loss of control of autonomous AI systems. In parallel, federal legislators in the US have proposed nascent 'AI incident regimes' to identify and counter similar threats. In this paper, we consolidate these two trends and present a timely proposal for a legally mandated post-deployment AI incident regime that aims to counter potential national security threats from AI systems. We start the paper by introducing the concept of 'security-critical' to describe sectors that pose extreme risks to national security, before arguing that 'security-critical' describes civilian nuclear power, aviation, life science dual-use research of concern, and frontier AI development. We then present in detail our AI incident regime proposal, justifying each component of the proposal by demonstrating its similarity to US domestic incident regimes in other 'security-critical' sectors. Finally, we sketch a hypothetical scenario where our proposed AI incident regime deals with an AI cyber incident. Our proposed AI incident regime is split into three phases. The first phase revolves around a novel operationalization of what counts as an 'AI incident' and we suggest that AI providers must create a 'national security case' before deploying a frontier AI system. The second and third phases spell out that AI providers should notify a government agency about incidents, and that the government agency should be involved in amending AI providers' security and safety procedures, in order to counter future threats to national security.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 8 of its 68 references that are in the map. First posted on arXiv 25 Mar 2025.

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8 of 68 references.

References · 8

  1. 2014Explaining and Harnessing Adversarial Examplescited by 7,364
  2. 2024GPT-4o System Cardcited by 4,588
  3. 2022The Alignment Problem from a Deep Learning Perspectivecited by 258
  4. 2023An Overview of Catastrophic AI Riskscited by 222
  5. 2023Spear Phishing With Large Language Modelscited by 52
  6. 2024Safety Cases: How to Justify the Safety of Advanced AI Systemscited by 48
  7. 2024Safety case template for frontier AI: A cyber inability argumentcited by 19
  8. 2017Automated Behavioral Analysis of Malware A Case Study of WannaCry Ransomwarecited by 10

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