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English(EN) PANOPTICON: A PII-Based Assemblage of Naturalistic Output Tokens for Investigating Privacy Leakage Within LLM Context Window

新的PANOPTICON数据集利用PII数据解决LLM隐私风险

研究人员开发了一个名为PANOPTICON的新管道和数据集,以应对研究大型语言模型(LLM)隐私风险的挑战。该数据集使用Meta的Llama-3.1-8B-Instruct模型生成,包含超过67,000个包含个人身份信息(PII)的提示,这些信息源自合成用户配置文件。该基准数据集旨在促进对提示反演攻击(PIA)的研究,并量化LLM上下文窗口内的隐私泄露,标志着LLM隐私研究向前迈出了重要一步。 AI

影响 能够对LLM隐私泄露和提示反演攻击进行定量研究,可能有助于更安全的LLM部署。

排序理由 该集群描述了一篇介绍用于LLM隐私研究的新数据集和方法论的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新的PANOPTICON数据集利用PII数据解决LLM隐私风险

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该集群描述了一篇介绍用于LLM隐私研究的新数据集和方法论的学术论文。[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) · Ryan Thornton, Mir Mehedi Ahsan Pritom, Maanak Gupta ·

    PANOPTICON:基于PII的自然化输出令牌汇编,用于调查LLM上下文窗口内的隐私泄露

    arXiv:2607.22695v1 Announce Type: new Abstract: Large Language Models (LLMs) are capable of generalizing human language for the completion of never-before-seen tasks, leading to widespread deployment. While this automation provides clear utility, completing these tasks often requ…