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Oct 12 · Monday

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  1. AttacksarXiv 2609.14649

    CIG-MIA:利用上下文信息增益对 RAG 系统发起成员推断攻击

    提出 CIG-MIA,用上下文信息增益推断 RAG 知识库成员身份

    Published
    Evaluated models
    Llama-3.1-8B-Instruct, Mistral-7B-Instruct-v0.3, Llama-2-13b-chat-hf and others6
    AbstractCIG-MIA 用注入前后的答案似然差推断 RAG 库成员,灰盒可分性高于所列基线。

    CIG-MIA 是针对 RAG 外部知识库的成员推断攻击,同时覆盖灰盒和纯文本黑盒。

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  2. AttacksarXiv 2609.12448

    GraphProfiler 用个人知识图谱推断敏感属性并溯源到具体帖子

    提出 GraphProfiler,用个人知识图谱从帖子历史推断敏感属性并溯源

    Published
    AbstractGraphProfiler 用源链接个人知识图谱做属性推断,准确率接近文本基线,并把证据定位到少量源帖。

    GraphProfiler 是一个可审计的 LLM 敏感属性画像器:用源链接个人知识图谱,把推断落到具体帖子。

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  3. AttacksarXiv 2607.01276

    研究者提出嵌入推断攻击 EIA,可在黑盒 IR 系统中识别所用嵌入模型

    提出嵌入推断攻击 EIA,在黑盒 IR 中识别所用嵌入模型

    Published
    Attacker
    Black-box
    Evaluated models
    e5-small, e5-small-v2, e5-base and others19
    AbstractEIA 用无序文档集的差异从候选中识别嵌入模型,并给出 reranker 与阈值下的计数。

    EIA 是在黑盒 IR 上识别所用嵌入模型的攻击。。

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  4. AttacksarXiv 2602.01757

    Zero2Text: Training-Free Cross-Domain Text Embedding Inversion Attack

    提出 Zero2Text,无需训练地跨域反演文本嵌入

    Published
    Attacker
    Black-box
    Evaluated models
    GTR-Base, Qwen3-Embedding-0.6B, Text-Embedding-3-small and others4
    Abstract零训练在线对齐可在未知域、无泄漏对时从黑盒 embedding 还原句子。

    Zero2Text 是一种不训练 decoder、也不使用泄漏文本–向量对的文本 embedding 反演,针对 RAG 向量库在严格黑盒、目标域未知时的还原。

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