#llm-privacy2 articles

2 articles

AIBullisharXiv – CS AI · 7h ago7/10

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ConfusionPrompt: Practical Private Inference for Online Large Language Models

Researchers introduce ConfusionPrompt, a privacy framework for large language models that decomposes user prompts into smaller sub-prompts mixed with pseudo-prompts before sending to cloud servers. The method protects user privacy while maintaining higher utility than existing perturbation-based approaches and works with existing black-box LLMs without modification.

AINeutralarXiv – CS AI · 7h ago6/10

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Say Something Else: Rethinking Contextual Privacy as Information Sufficiency

Researchers formalize privacy-preserving communication for LLM agents by introducing Information Sufficiency (IS) as a framework and proposing free-text pseudonymization as a third privacy strategy alongside suppression and generalization. Evaluation across 792 scenarios reveals that pseudonymization offers superior privacy-utility tradeoffs, and that multi-turn conversational testing exposes significant privacy leakage missed by single-message assessments.