Sobb Theresa, Turnbull Benjamin
School of Systems and Computing, University of New South Wales at the Australian Defence Force Academy, Campbell, ACT 2612, Australia.
Entropy (Basel). 2025 Jul 25;27(8):793. doi: 10.3390/e27080793.
Intelligent transport systems are revolutionising all aspects of modern life, increasing the efficiency of commerce, modern living, and international travel. Intelligent transport systems are systems of systems comprised of cyber, physical, and social nodes. They represent unique opportunities but also have potential threats to system operation and correctness. The emergent behaviour in Complex Cyber-Physical-Social Systems (C-CPSSs), caused by events such as cyber-attacks and network outages, have the potential to have devastating effects to critical services across society. It is therefore imperative that the risk of cascading failure is minimised through the fortifying of these systems of systems to achieve resilient mission assurance. This work designs and implements a programmatic model to validate the value of cascading failure simulation and analysis, which is then tested against a C-CPSS intelligent transport system scenario. Results from the model and its implementations highlight the value in identifying both critical nodes and percolation of consequences during a cyber failure, in addition to the importance of including social nodes in models for accurate simulation results. Understanding the relationships between cyber, physical, and social nodes is key to understanding systems' failures that occur because of or that involve cyber systems, in order to achieve cyber and system resilience.
智能交通系统正在彻底改变现代生活的方方面面，提高商业、现代生活和国际旅行的效率。智能交通系统是由网络、物理和社会节点组成的系统之系统。它们带来了独特的机遇，但也对系统运行和正确性构成潜在威胁。由网络攻击和网络中断等事件引发的复杂网络物理社会系统（C-CPSSs）中的突发行为，有可能对整个社会的关键服务造成毁灭性影响。因此，必须通过强化这些系统之系统来将级联故障的风险降至最低，以实现可靠的任务保障。这项工作设计并实现了一个编程模型，以验证级联故障模拟和分析的价值，然后针对一个C-CPSS智能交通系统场景进行测试。该模型及其实现的结果突出了在网络故障期间识别关键节点和后果渗透的价值，以及在模型中纳入社会节点以获得准确模拟结果的重要性。理解网络、物理和社会节点之间的关系是理解因网络系统或涉及网络系统而发生的系统故障的关键，以便实现网络和系统的弹性。
