Structural Vulnerability of Complex Networks Under Multiple Edge-Based Attacks

Author(s):  
Shudong Li ◽  
Xiaobo Wu ◽  
Aiping Li ◽  
Bin Zhou ◽  
Zhihong Tian ◽  
...  
2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Hao Peng ◽  
Wangxin Peng ◽  
Dandan Zhao ◽  
Zhaolong Hu ◽  
Jianmin Han ◽  
...  

Immunization strategies on complex networks are effective methods to control the spreading dynamics on complex networks, which change the topology and connectivity of the underlying network, thereby affecting the dynamics process of propagation. Here, we use a non-Markovian threshold model to study the impact of immunization strategies on social contagions, in which the immune index greater than (or equal to) 0 corresponds to targeted (random) immunization, and when the immune index is less than 0, the probability of an individual being immunized is inversely related to the degree of the individual. A generalized edge-based compartmental theory is developed to analyze the dynamics of social contagions under immunization, and theoretical predictions are very consistent with simulation results. We find that increasing the immune index or increasing the immune ratio will reduce the final adoption size and increase the outbreak threshold, in other words, make the residual network after immunization not conducive to social contagions. Interestingly, enhancing the network heterogeneity is proved to help improve the immune efficiency of targeted immunization. Besides, the dependence of the outbreak threshold on the network heterogeneity is correlated with the immune ratio and immune index.


2010 ◽  
Vol 389 (3) ◽  
pp. 595-603 ◽  
Author(s):  
Guo Chen ◽  
Zhao Yang Dong ◽  
David J. Hill ◽  
Guo Hua Zhang ◽  
Ke Qian Hua

2020 ◽  
Vol 8 (3) ◽  
Author(s):  
Furqan Aziz ◽  
Edwin R Hancock ◽  
Richard C Wilson

Abstract In this article, we present a novel approach to analyse the structure of complex networks represented by a quantum graph. A quantum graph is a metric graph with a differential operator (including the edge-based Laplacian) acting on functions defined on the edges of the graph. Every edge of the graph has a length interval assigned to it. The structural information contents are measured using graph entropy which has been proved useful to analyse and compare the structure of complex networks. Our definition of graph entropy is based on local edge functionals. These edge functionals are obtained by a diffusion process defined using the edge-based Laplacian of the graph using the quantum graph representation. We first present the general framework to define graph entropy using heat diffusion process and discuss some of its properties for different types of network models. Second, we propose a novel signature to gauge the structural complexity of the network and apply the proposed method to different datasets.


DYNA ◽  
2015 ◽  
Vol 82 (192) ◽  
pp. 68-77 ◽  
Author(s):  
Gabriel Jaime Correa-Henao ◽  
José María Yusta-Loyo

<p>The occurrence of impact events (e.g. blackouts with vast geographic coverage) into electrical critic infrastructure systems usually require the analysis of cascade failure root causes through the conduction of structural vulnerability studies, with well-defined methodologies that may guide decision-making for implementation of preventing actions and for operation recovering into the power system (e.g. N-1 and N-t contingency studies). This technical contribution provides some alternative techniques based upon complex networks and graph theory, which in the last few years have been proposed as useful methodologies for analysis of physical behavior of electric power systems. Vulnerability assessment is achieved by testing their performance into random risks and deliberate attacks threats scenarios. Results shown in this proposal lead to conclusions on the use of complex networks for contingency analysis by means of studies of those events that result in cascade failures and consumer disconnections.</p>


2018 ◽  
Vol 454 ◽  
pp. 164-181 ◽  
Author(s):  
Yi Wang ◽  
Junling Ma ◽  
Jinde Cao ◽  
Li Li

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