RAND Report: Multidimensional Approaches and Tiered Protection Strategies to Prevent Leakage of Core AI Algorithms
On July 20, 2026, Rand Inc. released the report “Protecting Algorithm Insights”. For the first time, it systematically examined algorithm insights as a strategically valuable asset that is difficult to control centrally, and established a five-tier security framework for algorithm insights ranging from basic security practices to highest-level physical isolation. This framework revolves around 44 attack vectors and five levels of adversary capabilities (OC1 to OC5), proposing a approach distinctly different from model weight protection: algorithm insights are dispersed across developer code, documentation, and people’s minds, resisting centralization. Their strategic value stems from the “power multiplier” effect, but they lack the characteristics of “size defense”. The report indicates that human intelligence collection is the highest-priority threat, while software and machine learning supply chain attacks using the low barriers of open-source ecosystems pose a indiscriminate threat. The five-tier framework (ISL1 to ISL5) corresponds one-to-one with adversary capabilities: ISL3 introduces zone isolation and internal threat prevention; ISL4 enforces critical security assumptions at the hardware level and tightens personnel measures; ISL5 represents the most stringent level of protection, requiring complete network isolation, independent supply chains, and…