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Oct 13 · Tuesday

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Found 3 papers
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Attack type

Poisoning and backdoors7Extraction and theft1Detection evasion2

System type

Models and APIs3

Attack surface / entry point

User input24Documents and messages8Images, audio and video10Training data3Weights and gradients9Inference services and hardware11

Layer

Model layer2Training and data layer8Infrastructure layer1
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Attack type：Extraction and theftAttack type：Detection evasionAttack surface / entry point：Training dataLayer：Model layerLayer：Infrastructure layerClear all

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  1. DefensesarXiv 2610.04426

    UnAct：无需梯度的定向激活干预实现类别遗忘

    提出 UnAct，仅以前向激活干预从分类器中遗忘指定类别

    arXiv
    2610.04426
    Published
    Layer
    Model layer
    Setting
    Models and APIs
    Evaluated models
    ResNet-18, ViT-B/16
    AbstractUnAct 用前向激活做类别遗忘。

    UnAct 是一种事后类别遗忘：删除请求可以只有少量该类图像，且没有标签和保留数据。它不用梯度，只对遗忘图像做前向。编辑对象是分类器所读的后期单元。

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  3. AttacksarXiv 2605.30040

    研究揭示 LLM 按 token 计费可被服务商系统性虚报

    构造可通过计费审计的 token 虚报，使服务商系统性超收

    arXiv
    2605.30040
    Published
    Layer
    Infrastructure layer
    Setting
    Models and APIs
    Evaluated models
    PALACE domain-adapted auditor
    Abstract不诚实提供方可在三种 token 审计上虚报并通过检查，作者认为需改用提供方不控制的证据。

    不透明 LLM 的按 token 计费里，现有审计核验的是提供方可控的证据，不诚实提供方可以虚报并通过检查。。

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