识别网络系统中针对连续攻击的临界点预警指标
Identifying early-warning indicators of tipping points in networked systems against sequential attacks
摘要：
在诸如社交网络、交通、电力和水分配基础设施以及生物和生态系统的广泛系统中的网络结构可以表现出临界阈值或临界点，超过该临界阈值或临界点，系统功能中存在不成比例的损失。人们越来越关注这种系统的临界点和故障容忍度，因为临界点可能导致预期功能的突然丧失和可能的不可恢复状态。虽然网络系统的攻击容忍度已经被深入研究的中断起源于一个单一的故障点，有这样的情况下，现实世界中的系统受到同时或突然发生的并发中断在多个位置。使用来自美国空域机场网络和印度铁路网络的开源数据，以及随机网络作为系统的原型类，我们研究了它们对不同大小的合成攻击策略的响应。对于这两种类型的网络，我们观察到存在的警告区域，这是一个前兆的临界点。此外，我们观察到网络的鲁棒性和同时分布的大小之间的统计显着的关系，这推广到具有不同拓扑属性的网络的随机故障和有针对性的攻击。我们表明，我们的方法可以确定不同架构的网络受到不同大小的中断的整体鲁棒性特征。我们的方法可以作为一种范式来理解现实世界系统中的临界点，该原则可以扩展到其他学科，以解决风险管理和弹性的关键问题。
英文摘要：
Network structures in a wide array of systems such as social networks, transportation, power and water distribution infrastructures, and biological and ecological systems can exhibit critical thresholds or tipping points beyond which there are disproportionate losses in the system functionality. There is growing concern over tipping points and failure tolerance of such systems as tipping points can lead to an abrupt loss of intended functionality and possibly non-recoverable states. While attack tolerance of networked systems has been intensively studied for the disruptions originating from a single point of failure, there have been instances where real-world systems are subject to simultaneous or sudden onset of concurrent disruption at multiple locations. Using open-source data from the United States Airspace Airport network and Indian Railways Network, and random networks as prototype class of systems, we study their responses to synthetic attack strategies of varying sizes. For both types of networks, we observe the presence of warning regions, which serve as a precursor to the tipping point. Further, we observe the statistically significant relationships between network robustness and size of simultaneous distribution, which generalizes to the networks with different topological attributes for random failures and targeted attacks. We show that our approach can determine the entire robustness characteristics of networks of disparate architecture subject to disruptions of varying sizes. Our approach can serve as a paradigm to understand the tipping point in real-world systems, and the principle can be extended to other disciplines to address critical issues of risk management and resilience.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
