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English(EN) PRISM: Generation-Time Detection and Mitigation of Secret Leakage in Multi-Agent LLM Pipelines

PRISM系统检测并阻止多智能体LLM管道中的秘密泄露

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了PRISM，一个旨在检测和缓解多智能体大型语言模型（LLM）管道中敏感信息泄露的新型防御系统。PRISM通过在每个生成步骤中实时分析16种不同的信号，来解决信息在智能体之间传播的风险（称为传播放大）。该方法结合了词汇、结构和行为特征来计算风险得分，从而能够进行逐令牌干预，并且性能显著优于现有防御措施。 AI

影响 引入了一种新颖的实时防御机制，用于保护复杂多智能体LLM系统中的敏感数据。

排序理由 该集群包含一篇研究论文，详细介绍了检测和缓解LLM管道中秘密泄露的新方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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PRISM系统检测并阻止多智能体LLM管道中的秘密泄露

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该集群包含一篇研究论文，详细介绍了检测和缓解LLM管道中秘密泄露的新方法。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Carsten Maple ·

    PRISM：多智能体LLM管道中生成时秘密泄露的检测与缓解

    Multi-agent LLM systems introduce a security risk in which sensitive information accessed by one agent can propagate through shared context and reappear in downstream outputs, even without explicit adversarial intent. We formalise this phenomenon as propagation amplification, whe…

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