arXiv cs.AI· Inderjeet Singh, Haitham Mahmoud, Andr\'es Murillo·· 1 天前AI 评分31
AI 沙箱的威胁模型、分类体系与测量框架
AI Sandboxes: A Threat Model, Taxonomy, and Measurement Framework
AI 导读
研究提出 AI 沙箱装置定义，区分五种相互重叠的原型，并给出十五个与主张相关的测量维度。其最弱环节授权规则将部署主张的上限限定在最弱的必要证据维度，并与覆盖外部危害和评估装置腐化的威胁模型相连接，应用于自动驾驶、工业控制、工具使用智能体和视觉-语言-动作操作四个实例。
正文 · 原文
Abstract:AI sandboxes produce evidence about systems that may act through software tools, networked devices, or physical actuators. The interpretation of that evidence depends on the boundary of the experiment. We define a sandbox apparatus, distinguish five overlapping archetypes, and specify fifteen claim-relative measurement dimensions. A weakest-link licensing rule caps a deployment claim at its weakest necessary evidence dimension. We connect this rule to a threat model covering both outward harm and corruption of the evaluation apparatus, then apply it to four worked examples spanning driving, industrial control, tool-using agents, and vision-language-action manipulation. We also map the required artifacts to standards and regulatory instruments. The framework identifies which claims a bounded experiment supports, which failures its controls contain, and which assumptions require further validation before deployment.
| Comments: | 42 pages, 8 figures, 7 tables |
| Subjects: | Cryptography and Security (cs.CR); Artificial Intelligence (cs.AI); Robotics (cs.RO); Software Engineering (cs.SE) |
| Cite as: | arXiv:2606.18532 [cs.CR] |
| (or arXiv:2606.18532v2 [cs.CR] for this version) | |
| https://doi.org/10.48550/arXiv.2606.18532 arXiv-issued DOI via DataCite |
Submission history
From: Inderjeet Singh [view email]
[v1]
Tue, 16 Jun 2026 22:57:24 UTC (1,985 KB)
[v2]
Tue, 10 Nov 2026 22:45:06 UTC (1,996 KB)
来源：arXiv cs.AI · arxiv.org