English(EN) LogiC-Diff: Embedding Security Properties Into AI-Enabled Cyber-Physical Systems

新的LogiC-Diff框架将安全属性嵌入支持AI的网络物理系统

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-01 04:00

研究人员开发了LogiC-Diff，一个新颖的框架，可将安全属性直接嵌入支持AI的网络物理系统（CPS）。该方法使用逻辑条件双阶段扩散将信号时序逻辑（STL）规范集成到预测过程中。LogiC-Diff旨在减轻对抗性扰动并强制执行期望的时序行为，从而增强CPS在各种攻击下的鲁棒性和规范遵从性。 AI

影响增强控制物理过程的AI系统的安全性和可靠性，这对于安全关键型应用至关重要。

排序理由该集群包含一篇详细介绍新技术框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.AI TIER_1 English(EN) · Ziyan An, John Stankovic, Meiyi Ma · 2026-10-01 04:00

LogiC-Diff：将安全属性嵌入支持AI的网络物理系统

arXiv:2609.38381v1 Announce Type: cross Abstract: AI-enabled Cyber-Physical Systems (CPS) are highly vulnerable to adversarial and anomalous inputs, where small perturbations can induce cascading errors and unsafe control actions. Existing approaches, such as rule-based filtering…