Application of modal analysis in assessing attack vulnerability of complex networks

Petreska, Irina; Tomovski, Igor; Gutiérrez, Eugenio; Kocarev, Ljupčo; Flavio, Bono; Karmen, Poljansek

doi:10.1016/j.cnsns.2009.05.002

Cited by 25 publications

(21 citation statements)

References 17 publications

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“…Identified the critical airports for the global ATN of November 2011-November 2012 [15]. Irina Petreska et al started from the similarity of structural dynamics and complex networks, the network node/link busy degree is proposed on the basis of the modal equation, which could be used as the measure of vulnerability reflecting the influence on neighboring nodes [25]. Sun, D. et al defined that the station vulnerability is the change of the topological efficiency and the influence of passenger flow after attacked, as well as the probability of station being attacked.…”

Section: Literature Reviewmentioning

confidence: 99%

Network Vulnerability Analysis of Rail Transit Plans in Beijng-Tianjin-Hebei Region Considering Connectivity Reliability

Liu

et al. 2017

Sustainability

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Abstract:In the context of the urban agglomeration and the rapid development of rail transit, the planning of the Beijing-Tianjin-Hebei Region (BTHR) rail transit 2020 is attracting attention. The BTHR is a natural disaster-prone area and a high-risk area for terrorist attacks; the robustness of the area is critical to the sustainable development of North China. Therefore, it is necessary to analyze the vulnerability of the regional planning rail transit network. This paper builds a model of planning regional rail transit in BTHR. A critical node recognition measure is designed according to the connectivity reliability of nodes. The method of Monte Carlo simulation of node connectivity reliability is applied based on link connectivity probability. In addition, a model of detecting multi-measure recognition and detecting Core-Nodes is proposed. Finally, the paper analyzes the impact of multiple attack modes on the network performance from the aspects of network performance within region and transit demand outside the region, and analyzes the vulnerability of the BTHR planning rail transit network.

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Section: Literature Reviewmentioning

confidence: 99%

Network Vulnerability Analysis of Rail Transit Plans in Beijng-Tianjin-Hebei Region Considering Connectivity Reliability

Liu

et al. 2017

Sustainability

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“…Network robustness can be assessed through the effect of the isolation of a fraction f of nodes on the size of the network's giant component (ie, the connected subset of the network with the highest number of nodes). The network will be robust when the size of the giant component decreases little for relatively high values of f (Petreska et al, 2010;Mishkovski et al, 2011). The nodes to isolate can be selected either at random (errors) or through a criterion usually based on node centrality (attacks) (Albert et al, 2000) The study of the robustness allows to evaluate the capacity of a network to avoid a malfunction when a fraction of its components is damaged (Boccaletti et al, 2006).…”

Section: Methodsmentioning

confidence: 99%

Robustness of airline route networks

Lordan

Sallán

Escorihuela

et al. 2016

Physica A: Statistical Mechanics and its Applications

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Airlines shape their route network by defining their routes through supply and demand considerations, paying little attention to network performance indicators, such as network robustness. However, the collapse of an airline network can produce high financial costs for the airline and all its geographical area of influence. The aim of this study is to analyze the topology and robustness of the network route of airlines following Low Cost Carriers (LCC) and Full Service Carriers (FSC) business models. Results show that FSC hubs are more central than LCC bases in their route network. As a result, LCC route networks are more robust than FSC networks.Peer ReviewedPostprint (author's final draft

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“… These problems are of central importance in the study of social networks [3, 10], which have received substantial attention in the past decade since the introduction of the “small‐world network” concept [58]. The term was originally proposed to demonstrate the small‐world phenomenon arising in collaboration networks but has also shown promise in describing complex systems in biology, sociology, economics, and medicine [47, 48]. Latora and Marchiori [35] and Crucitti et al [18] emphasize the importance of studying vulnerability and protecting such networks.…”

Section: Introductionmentioning

confidence: 99%

Polynomial‐time algorithms for solving a class of critical node problems on trees and series‐parallel graphs

Shen¹,

Smith²

2011

Networks

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We examine variants of the critical node problem on specially structured graphs, which aim to identify a subset of nodes whose removal will maximally disconnect the graph. These problems lie at the intersection of network interdiction and graph theory research and are relevant to several practical optimization problems. The two different connectivity metrics that we consider regard the number of maximal connected components (which we attempt to maximize) and the largest component size (which we attempt to minimize). We develop optimal polynomial-time dynamic programming algorithms for solving these problems on tree structures and on series-parallel graphs, corresponding to each graphconnectivity metric. We also extend our discussion by considering node deletion costs, node weights, and solving the problems on generalizations of tree structures. Finally, we demonstrate the computational efficacy of our approach on randomly generated graph instances.

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Application of modal analysis in assessing attack vulnerability of complex networks

Cited by 25 publications

References 17 publications

Network Vulnerability Analysis of Rail Transit Plans in Beijng-Tianjin-Hebei Region Considering Connectivity Reliability

Network Vulnerability Analysis of Rail Transit Plans in Beijng-Tianjin-Hebei Region Considering Connectivity Reliability

Robustness of airline route networks

Polynomial‐time algorithms for solving a class of critical node problems on trees and series‐parallel graphs

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