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Dependency-based targeted attacks in interdependent networks.
Physical Review E ( IF 2.2 ) Pub Date : 2020-08-03 , DOI: 10.1103/physreve.102.022301
Dong Zhou 1, 2 , Amir Bashan 3
Affiliation  

Modern large engineered network systems normally work in cooperation and incorporate dependencies between their components for purposes of efficiency and regulation. Such dependencies may become a major risk since they can cause small-scale failures to propagate throughout the system. Thus, the dependent nodes could be a natural target for malicious attacks that aim to exploit these vulnerabilities. Here we consider a type of targeted attack that is based on the dependencies between the networks. We study strategies of attacks that range from dependency-first to dependency-last, where a fraction 1p of the nodes with dependency links, or nodes without dependency links, respectively, are initially attacked. We systematically analyze, both analytically and numerically, the percolation transition of partially interdependent networks, where a fraction q of the nodes in each network are dependent on nodes in the other network. We find that for a broad range of dependency strength q, the “dependency-first” attack strategy is actually less effective, in terms of lower critical percolation threshold pc, compared with random attacks of the same size. In contrast, the “dependency-last” attack strategy is more effective, i.e., higher pc, compared with a random attack. This effect is explained by exploring the dynamics of the cascading failures initiated by dependency-based attacks. We show that while “dependency-first” strategy increases the short-term impact of the initial attack, in the long term the cascade slows down compared with the case of random attacks and vice versa for “dependency-last.” Our results demonstrate that the effectiveness of attack strategies over a system of interdependent networks should be evaluated not only by the immediate impact but mainly by the accumulated damage during the process of cascading failures. This highlights the importance of understanding the dynamics of avalanches that may occur due to different scenarios of failures in order to design resilient critical infrastructures.

中文翻译:

相互依赖的网络中基于依赖的有针对性的攻击。

现代大型工程网络系统通常协同工作,并在其组件之间合并依赖关系,以实现效率和监管目的。这样的依赖关系可能会成为主要风险,因为它们可能导致小规模故障在整个系统中传播。因此,从属节点可能成为旨在利用这些漏洞的恶意攻击的自然目标。在这里,我们考虑一种基于网络之间依赖性的有针对性的攻击。我们研究的攻击策略范围从“依赖关系优先”到“依赖关系最后”,其中一小部分1个-p首先,分别攻击具有依赖关系链接的节点或没有依赖关系链接的节点。我们从分析和数值两个方面系统地分析了部分相互依赖的网络的渗透过渡,其中一部分q每个网络中节点的数量取决于另一个网络中的节点。我们发现对于广泛的依赖强度q,就较低的临界渗透阈值而言,“依赖关系优先”的攻击策略实际上效果较差 pC,与相同大小的随机攻击相比。相反,“最后依赖”攻击策略更有效,即更高pC,与随机攻击相比。通过研究由基于依赖项的攻击引发的级联故障的动态来解释这种影响。我们表明,尽管“依赖优先”策略增加了初始攻击的短期影响,但从长远来看,与随机攻击相比,级联速度有所降低,而“依赖最后”则反之。我们的结果表明,相互依赖的网络系统上的攻击策略的有效性不仅应通过直接影响来评估,而且还应主要通过级联故障过程中的累积损害来评估。这凸显了理解因故障情况不同而可能发生的雪崩动态的重要性,以设计弹性关键基础架构。
更新日期:2020-08-03
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