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Oct 12 · Monday
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About this collection Collection in progress We are building a large AI safety paper collection to help researchers find work related to their interests. Papers are collected automatically andfiltered only for relevance to AI safety , without judging quality, novelty or reading value. The default “Annotated first” shows papers with tags or published paper analyses first. Each group is ordered by original publication date, newest first, with undated papers last. “Newest first” uses publication dates only. This order is not a quality ranking.
One-line summaries, tags and paper analyses are prepared by AI from the papers. Language models may have systematic biases and produce hallucinations.We plan to carry out human annotation and review to reduce errors in this content.
量化片外功耗测量对隐藏算力的约束能力
Published Oct 6 Abstract 作者称功耗单独只能弱约束隐藏算力。这篇工作定量估计片外功耗能为算力核验排除多少未声明运算。
用 SCM 合成会话并训练检测器识别推理层滥用
Published Sep 29
Evaluated models gradient-boosted detector (GBDT/XGBoost) 提出 GIFT,用加密与 GPU 信息流跟踪隔离共享 LLM 服务中的用户数据
Published Aug 26
Evaluated models Qwen2.5-14B , Qwen2.5-32B , Qwen2.5-72B and others6 Abstract GIFT 以加密隔离加 GPU 信息流规则,在 vLLM 与 DistServe 上强制用户数据隔离,并报告了吞吐开销。GIFT 是作者为共享 LLM serving 做的用户数据隔离系统,并有启用机密计算的 GIFT-CC。作者在结论中称它是该场景的首个 IFT 设计。
提出 CodeSpear 越狱,借语法约束解码生成恶意代码,并给出 CodeShield 防御
Published Jun 10
Evaluated models Qwen2.5-Coder-7B , Qwen2.5-Coder-32B , Qwen2.5-7B and others10 Abstract 论文发现语法约束解码会破坏自然语言安全对齐,提出 CodeSpear 越狱攻击与基于蜜罐代码对齐的 CodeShield 防御。
提出 SeedHijack,劫持采样 PRNG 以强制选定 token
Published May 8
Evaluated models GPT-2 (124M) , Qwen2-1.5B-Instruct , DeepSeek-R1-1.5B and others5 Abstract 采样层 PRNG 被替换以强制选 token。SeedHijack 把 LLM 采样用的 PRNG 输出换成攻击者选定的数,从而指定下一个 token。权重、输入和 logits 都不改。防御是用硬件 QRNG 替换该随机源。
提出 PrefixWall 选择性隔离共享前缀以缓解计时侧信道
Published Mar 11
Evaluated models gemma-3-4b-it , llava-onevision-qwen2-0.5b-ov-hf , llava-onevision-qwen2-7b-ov-chat-hf and others9 Abstract PrefixWall 用缓存元数据按需切断跨用户前缀延续,以保留 APC 并限制 TTFT 侧信道。PrefixWall 是多租户 LLM 服务上的系统级防御,用来限制 Automatic Prefix Caching 的 TTFT 侧信道,同时保留前缀复用。
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