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English(EN) ShadowFPT: Backdooring Federated Prompt Tuning via Shadow Triggers

新的ShadowFPT攻击利用了联邦提示调优中冻结的主干网络

研究人员开发了一种名为ShadowFPT的新后门攻击,该攻击针对大型视觉语言模型中的联邦提示调优(FPT)。该攻击利用了模型的冻结主干网络,允许恶意客户端通过优化针对冻结编码器的“影子触发器”来注入后门行为。该触发器将触发的输入错误地引导至表示空间中的目标类别,而客户端的提示更新则保持隐蔽。ShadowFPT在保持干净准确率的同时显著提高了攻击成功率,表明仅关注提示更新异常的防御措施是不够的。 AI

影响 突显了联邦学习在大型语言模型方面的新漏洞,可能需要新的防御机制。

排序理由 详细介绍AI模型新攻击方法的学术论文。[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ShadowFPT攻击利用了联邦提示调优中冻结的主干网络

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详细介绍AI模型新攻击方法的学术论文。[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) · Kun Zhai, Teng Li, Yunhao Feng, Xingjun Ma ·

    ShadowFPT:通过影子触发器对联邦提示调优进行后门攻击

    arXiv:2610.22871v1 Announce Type: new Abstract: Federated Prompt Tuning (FPT) adapts large vision--language models by freezing the pretrained backbone and optimizing only lightweight prompt parameters across clients. Although this design improves communication and parameter effic…