Precise Monitoring of Cyber-Physical Technology under Uncertainty(PreCePT)

不确定性下信息物理技术的精确监控（PreCePT）

• 批准号: 521273327
• 负责人: Professor Dr. Bernd Finkbeiner
• 金额: --
• 依托单位: Forschungsgebiet Zuverlässige Sicherheitsgarantien
• 依托单位国家: 德国
• 项目类别: Research Grants
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/521273327?language=en
• 关键词: Precise; Monitoring; Cyber; Physical; Technology

Cyber-Physical Systems (CPS) joining a physical environment and numerous embedded computational devices via digital networking into a tightly coupled system are rapidly becoming reality. They are at the heart of the recent push towards so-called smart environments. Most of these applications are inherently safety-critical in that malfunctions may endanger life, property, or the environment. The quest for ensuring the predictable, reliable, and safe operation of complex cyber-physical infrastructures is often addressed via stringent run-time monitoring. The applications pose high demands on the accuracy of the monitoring mechanisms, as lacking detection of an anomaly in system behaviour may induce the aforementioned risks, while spurious signalling of a potential problem may lead to performance-degrading exception handling up to full system lock-down. The PreCePT project addresses these demands by rigorously bridging formal methods and metrology in that it provides automatic generation of run-time monitors from formal specifications, with the generated monitors being faithful to the inevitable and significant inaccuracies and uncertainties arising when observing physical state through actual sensor devices. It develops best-in-class algorithms for the automatic monitoring of durational spatio-temporal properties under epistemic as well as aleatory uncertainties. These algorithms reconcile maximal exactness given the inaccuracies and partiality of the sensory equipment with hard real-time guarantees for their execution on embedded hardware in-situ. They are based on rigorous semantic models of both CPS dynamics and sensory equipment and on the use of advanced arithmetic constraint-solving technology, and are consequently provably optimal.

网络物理系统（CPS）通过数字网络将物理环境和众多嵌入式计算设备连接到紧密耦合的系统中正在迅速成为现实。它们是最近推动所谓智能环境的核心。这些应用中的大多数本质上是安全关键的，因为故障可能危及生命、财产或环境。确保复杂网络物理基础设施的可预测、可靠和安全运行的要求通常通过严格的运行时监控来解决。应用程序对监测机制的准确性提出了很高的要求，因为缺乏对系统行为异常的检测可能会引发上述风险，而潜在问题的虚假信号可能会导致性能下降的异常处理，直至完全系统锁定。PreCePT项目通过严格桥接正式方法和计量学来满足这些需求，因为它提供了从正式规范自动生成运行时监视器，生成的监视器忠实于通过实际传感器设备观察物理状态时产生的不可避免的和显著的不准确性和不确定性。它开发了同类最佳的算法，用于在认知和偶然不确定性下自动监测持续时间的时空特性。这些算法调和最大的准确性给定的不准确性和硬实时保证他们的嵌入式硬件上执行的传感设备。他们是基于严格的语义模型的CPS动力学和感官设备，并使用先进的算术约束求解技术，因此可证明是最佳的。