Skip to content

Translation in progress Some entries still include text in the original language.

Oct 12 · Monday

All papers

Found 4 papers
Filter2

Defense type

Model hardening3Inference-time intervention3Detection and filtering22Instruction–data separation5Permissions and approval4Monitoring and auditing3

System type

LLM applications4AI Agent68coding agent11science agent3web agent3Multi-agent systems9

Layer

Application layer3
Select any value within a category; different categories must all match. Counts include the other filters you have selected.Another 265papers have no tags yet and are not included in filtered results.
Defense type：Permissions and approvalSystem type：LLM applicationsClear all

Another 265papers do not have category tags yet and are not included in filtered results.

  2. DefensesarXiv 2610.02432

    论文提出 LLM 输入扰动鲁棒性度量，并发布 ASA 攻击与 AttestMCP 防护

    提出 ASA 与 AttestMCP，度量并降低 LLM 对输入序列扰动的敏感

    arXiv
    2610.02432
    Published
    Layer
    Application layer
    Setting
    LLM applications, AI Agent
    Attacker
    Black-box
    Evaluated models
    Gemma-3-27B-Instruct, Gemma-3-4B-Instruct, Llama-3.2-3B-Instruct and others12
    Paper analysisRead analysis
  4. DefensesarXiv 2609.04159

    Sentinel-RL：将拓扑推理从 LLM 智能体中卸载到安全运营中心

    提出 Sentinel-RL，将拓扑处置从 LLM 卸载到受约束图策略

    arXiv
    2609.04159
    Published
    Layer
    Application layer
    Setting
    LLM applications
    Evaluated models
    HetGAT, PPO
    AbstractSentinel-RL 用图编码器与 PPO 承担拓扑决策，LLM 负责叙述与门控，并在 LANL 上报告检测与时延。

    Sentinel-RL 是面向 SOC 的神经符号架构：拓扑决策离开 LLM，改由认证图上的 HetGAT 与 PPO 完成。

    Paper analysisRead analysis
You have reached the end