Privacy in Large Language Models: Attacks, Defenses and Future Directions

Understand

The advancement of large language models (LLMs) has significantly enhanced the ability to effectively tackle various downstream NLP tasks and unify these tasks into generative pipelines.

• On the one hand, powerful language models, trained on massive textual data, have brought unparalleled accessibility and usability for both models and users.
• On the other hand, unrestricted access to these models can also introduce potential malicious and unintentional privacy risks.
• Despite ongoing efforts to address the safety and privacy concerns associated with LLMs, the problem remains unresolved.