Chain-of-Authorization: Internalizing Authorization into Large Language Models via Reasoning Trajectories

📰 ArXiv cs.AI

Researchers propose Chain-of-Authorization, a method to internalize authorization into Large Language Models via reasoning trajectories to prevent sensitive data leakage

advanced Published 25 Mar 2026

Action Steps

Identify sensitive data and access boundaries within the LLM's knowledge graph
Implement reasoning trajectories to track data provenance and ownership
Integrate authorization mechanisms into the LLM's architecture to restrict access to sensitive data
Evaluate and refine the Chain-of-Authorization approach through experiments and testing

Who Needs to Know This

AI engineers and researchers working on LLMs can benefit from this approach to improve the security and reliability of their models, while data scientists and security experts can apply this method to protect sensitive data

Key Insight

💡 Internalizing authorization into LLMs can prevent sensitive data leakage and adversarial manipulation