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English(EN) Behavioral Privacy Leakage in Agentic Negotiation: Formalizing and Mitigating Inference Attacks via Randomized Policies

苹果研究人员发布隐私保护的协商策略

作者 PulseAugur 编辑部 · [1 个来源] ·

Apple Machine Learning Research 发表了一篇论文，详细介绍了一种在自主代理协商过程中保护私人信息的新方法。该研究引入了一种自适应随机协商策略，旨在确保差分隐私、保证协议收敛并保持高协商效用。实验表明，该方法在保持超过90%的协商成功率和效用的同时，显著降低了对抗性推理的准确性。 AI

影响 引入了一种在人工智能驱动的协商中保护敏感数据的新方法，有可能增强对自主系统的信任。

排序理由 苹果研究部门发布的关于一种新颖的隐私保护技术的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 Apple Machine Learning Research 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

苹果研究人员发布隐私保护的协商策略

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苹果研究部门发布的关于一种新颖的隐私保护技术的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. Apple Machine Learning Research TIER_1 English(EN) ·

    Agentic Negotiation中的行为隐私泄露：通过随机策略形式化和缓解推理攻击

    This paper was accepted at the AI4TCI (Workshop on AI for Secure and Trustworthy Critical Infrastructure Systems) Workshop at the International Conference on Availability, Reliability and Security (ARES) 2026. Autonomous negotiation agents are increasingly deployed in high-stakes…

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