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English(EN) When Emotion Becomes Trigger: Emotion-style dynamic Backdoor Attack Parasitising Large Language Models

新型后门攻击利用LLM的情感风格

研究人员开发了一种名为Paraesthesia的新型后门攻击,通过利用输入中的情感风格来针对大型语言模型(LLM)。与依赖固定触发器的先前攻击不同,Paraesthesia将其恶意条件编码在文本的情感基调中,在各种任务和LLM上实现了超过98.25%的攻击成功率。该方法表明,情感风格可以作为后门的触发面,区别于传统的词汇或语法模式,并且能够抵御多种防御机制。 AI

影响 识别出LLM的一种新型攻击向量,可能影响模型安全和当前防御策略的有效性。

排序理由 详细介绍LLM新攻击方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

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新型后门攻击利用LLM的情感风格

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详细介绍LLM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.CL TIER_1 English(EN) · Ziyu Liu, Tao Li, Tao Yang, Tianjie Ni, Xiaolong Lan, Wengang Ma, Junjiang He ·

    当情绪成为触发器:情绪风格的动态后门攻击寄生于大型语言模型

    arXiv:2605.11612v2 Announce Type: replace Abstract: Data-poisoning backdoors pose a practical threat to the fine-tuning of large language models (LLMs). Most existing attacks bind an attacker-selected behavior to fixed tokens, phrases, scenarios, or syntactic structures. These di…