Software Intelligence Engineering Laboratory, Department of Computer Science, Chungbuk National University, Cheongju 28644, Korea.
Sensors (Basel). 2022 Jun 13;22(12):4474. doi: 10.3390/s22124474.
The System of Cyber-Physical Systems (SoCPS) comprises several independent Cyber-Physical Systems (CPSs) that interact with each other to achieve a common mission that the individual systems cannot achieve on their own. SoCPS are rapidly gaining attention in various domains, e.g., manufacturing, automotive, avionics, healthcare, transportation, and more. SoCPS are extremely large, complex, and safety-critical. As these systems are safety-critical in nature, it is necessary to provide an adequate safety analysis mechanism for these collaborative SoCPS so that the whole network of these CPSs work safely. This safety mechanism must include composite safety analysis for a network of collaborative CPS as a whole. However, existing safety analysis techniques are not built for analyzing safety for dynamically forming networks of CPS. This paper introduces a composite safety analysis approach called SafeSoCPS to analyze hazards for a network of SoCPS. In SafeSoCPS, we analyze potential hazards for the whole network of CPS and trace the faults among participating systems through a fault propagation graph. We developed a tool called SoCPSTracer to support the SafeSoCPS approach. Human Rescue Robot System-a collaborative system-is taken as a case study to validate our proposed approach. The result shows that the SafeSoCPS approach enables us to identify 18 percent more general faults and 63 percent more interaction-related faults in a network of a SoCPS.
赛博物理系统（SoCPS）由多个相互作用的独立的赛博物理系统（CPS）组成，以实现单个系统无法独自实现的共同任务。SoCPS 在制造、汽车、航空电子、医疗保健、交通等各个领域迅速受到关注。SoCPS 非常庞大、复杂且对安全性要求极高。由于这些系统本质上具有安全性要求，因此需要为这些协作性 SoCPS 提供充分的安全分析机制，以确保这些 CPS 网络的整体安全运行。这种安全机制必须包括对协作性 CPS 网络的综合安全分析。然而，现有的安全分析技术并不是为分析动态形成的 CPS 网络的安全性而构建的。本文引入了一种称为 SafeSoCPS 的综合安全分析方法，用于分析 SoCPS 网络的危险。在 SafeSoCPS 中，我们通过故障传播图分析整个 CPS 网络的潜在危险，并跟踪参与系统之间的故障。我们开发了一个名为 SoCPSTracer 的工具来支持 SafeSoCPS 方法。人机救援机器人系统——一个协作系统——被作为案例研究来验证我们提出的方法。结果表明，SafeSoCPS 方法能够使我们在 SoCPS 网络中识别出 18%更多的一般故障和 63%更多的交互相关故障。
