GoldCoin: Grounding Large Language Models in Privacy Laws via Contextual Integrity Theory

Understand

Privacy issues arise prominently during the inappropriate transmission of information between entities.

• Existing research primarily studies privacy by exploring various privacy attacks, defenses, and evaluations within narrowly predefined patterns, while neglecting that privacy is not an isolated, context-free concept limited to traditionally sensitive data (e.g., social security numbers), but intertwined with intricate social contexts that complicate the identification and analysis of potential privacy violations.
• The advent of Large Language Models (LLMs) offers unprecedented opportunities for incorporating the nuanced scenarios outlined in privacy laws to tackle these complex privacy issues.
• However, the scarcity of open-source relevant case studies restricts the efficiency of LLMs in aligning with specific legal statutes.