PromptGraph: Graph-Guided Prompt Sanitization for Balancing Privacy and Utility in LLM Inference
Large Language Model (LLM) services introduce a fundamental privacy challenge. Sensitive information may be inferred not only from explicit identifiers, such as names or phone numbers, but also from contextual associations among otherwise innocuous spans. Existing sanitizers typically assign privacy or utility signals to individual spans without explicitly modeling pairwise relationships among them. In this paper, we propose PromptGraph, a graph-guided prompt-sanitization approach for privacy-preserving LLM inference. PromptGraph estimates privacy leakage at the span level and utility-relevant contextual dependencies between pairs of spans. It represents each prompt as an attributed graph...
| Authors | Chen Gu, Hui Wan, Donghui Hu et al. |
|---|---|
| Primary category | cs.CR |
| Published | 12 July 2026 |
| Last updated at source | 12 July 2026 |
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