New AdvGuard framework combats LLM prompt leakage attacks

Researchers have developed AdvGuard, a novel framework designed to detect and mitigate prompt leakage attacks against large language models (LLMs). These attacks aim to extract confidential system prompts that guide LLM behavior. AdvGuard utilizes a graph convolutional network (GCN) to model relationships between user queries, identifying malicious patterns that emerge across multiple interactions. The framework also includes a prompt-level detector for immediate protection and has demonstrated high accuracy in evaluations, significantly reducing the success rate of known and unseen attack families. AI

IMPACT Enhances LLM security by providing a robust defense against prompt leakage, crucial for protecting proprietary information and ensuring model integrity.

RANK_REASON Academic paper detailing a new method for LLM security. [lever_c_demoted from research: ic=1 ai=1.0]

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• AdvGuard
• arXiv
• graph convolutional network
• large-language models

• paper
• safety

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