Behavioral Privacy Leakage in Agentic Negotiation: Formalizing and Mitigating Inference Attacks via Randomized Policies

• 类型：arxiv
• 标识：2607.06815
• 链接：https://arxiv.org/abs/2607.06815
• 主分类：agent
• 形态：application
• 被引：0
• 被引来源：Semantic Scholar
• S2被引：0
• 影响力被引：0
• TLDR：This paper designs an adaptive stochastic negotiation policy that jointly guarantees behavioral differential privacy, almost-sure convergence of the offer sequence, and high negotiation utility, and demonstrates that strong privacy guarantees can be achieved without significant loss of performance.
• 副分类：llm-infra
• 待LLM分类：否
• 标题中文：Agentic 谈判中的行为隐私泄露：通过随机化策略形式化与缓解推理攻击
• TLDR中文：本文设计了一种自适应随机谈判策略，同时保证行为差分隐私、报价序列的几乎处处收敛以及较高的谈判效用，并证明在获得强隐私保证的同时不会带来显著的性能损失。
• 来源文件：
• /inbox/tom/_candidates/2026-07-21-rag-retrieval-reranking-candidates.json
• /inbox/tom/_candidates/2026-07-21-agent-rag-longcontext-candidates.json
• [S2 enrich]