LLM Anonymization Against Agentic Re-Identification
Agentic LLMs allow re-identification through cross-referencing rich context, rendering standard anonymization defenses inadequate. AURA is an LLM framework that iteratively masks text based on privacy inferences while simultaneously evaluating candidate rewrites for both privacy resistance and utility preservation. This decouples the process, showing how to balance strong privacy against retaining valuable analytic information.