通过形式化分析与架构分解,展示 SSGM 如何缓解拓扑引发的知识泄漏(敏感上下文被固化到长期存储),以及有助于防止语义漂移(知识在迭代摘要中退化)。Through formal analysis and architectural decomposition, it is shown how SSGM can mitigate topology-induced knowledge leakage where sensitive contexts are solidified into long-term storage, and help prevent semantic drift where knowledge degrades through iterative summarization.
论文
3 张论文卡片 · 安全与风险 · OA 绿色
SSGM框架(Stability and Safety-Governed Memory)
3. SSGM框架(Stability and Safety-Governed Memory)
1. Data Flow Control(DFC):AI Agent 数据安全策略的内核级执行框架
本文将数据安全形式化为 provenance monomials 上的聚合谓词,并提出 Passant——一个无需物化 provenance 即可强制执行 DFC 策略的可移植查询重写层。This paper formalizes data safety as aggregate predicates over provenance monomials and presents Passant, a portable query rewriting layer that enforces DFC policies without materializing provenance.
4.2 Reliability 不等于成功率:12 指标拆出 consistency / robustness / predictability / safety
4.2 Reliability 不等于成功率:12 指标拆出 consistency / robustness / predictability / safety(⭐⭐⭐⭐⭐)
本工作提出 12 个具体指标,从一致性、鲁棒性、可预测性和安全性四个关键维度分解 Agent 可靠性,可与传统评估互补,并提供用于分析 Agent 表现、退化与失败方式的工具。This work proposes twelve concrete metrics that decompose agent reliability along four key dimensions: consistency, robustness, predictability, and safety, which complement traditional evaluations while offering tools for reasoning about how agents perform, degrade, and fail.