智能数据安全:数据驱动的网络物理系统的在线安全模型

José Luís Conradi Hoffmann, A. A. Fröhlich
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引用次数: 2

摘要

当代网络物理系统(CPS),如自动驾驶汽车,主要由数据驱动。在这种数据驱动系统中,将时序和数据语义结合起来是保证安全的关键。本文提出了SmartData的扩展,以支持在线安全监测。通过遵循数据驱动设计,我们推广了使用包含安全模型的信号时序逻辑(STL)的属性监视器规范。时序方面从STL规范根源于SmartData固有的时序数据。财产监视器被设想为安全执行单元(SEU)内部的在线监控方法。SEU周期性地保证时间和语义的可满足性。我们通过使用SmartData建模的自动驾驶汽车的案例研究来演示所提出的设计。案例研究将Mobileye的责任敏感安全(Responsibility-Sensitive Safety)作为车辆安全状况的标尺。最后,通过探索将STL规范解释为遵循RTAMT库的属性监视器,该设计提供了SEU内部的在线验证功能。
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SmartData Safety: Online Safety Models for Data-Driven Cyber-Physical Systems
Contemporary Cyber-Physical Systems (CPS), such as autonomous vehicles, are driven mainly by data. Combining timing and data semantics in such Data-Driven systems is crucial to assure safety. This paper proposes an extension of SmartData to support online safety monitoring. By following a Data-Driven Design, we promote a specification of property monitors using Signal Temporal Logic (STL) encompassing Safety Models. Timing aspects from STL specification roots from the timed data intrinsic to SmartData. The property monitors are envisioned as an online monitoring method inside a Safety Enforcement Unit (SEU). The SEU periodically assures the satisfiability of timing and semantics. We demonstrate the proposed design through a case study of an autonomous vehicle modeled using SmartData. The case study considers Mobileye’s Responsibility-Sensitive Safety as a ruler for safety vehicle conditions. Finally, the design provides the online verification capabilities inside the SEU by exploring the interpretation of STL specification as property monitors following the RTAMT library.
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