Cascading failure of interdependent networks with different coupling preference under targeted attack

Chen, Zhen; Wei, Du; Cao, Xianbin; Zhou, Xing-Lian

doi:10.1016/j.chaos.2015.03.005

Cited by 84 publications

(37 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Cascading effects of some real‐world hazards such as earthquakes, terrorist attacks like economic effects of the 9/11 attack (for example, the considerable disorder in international trade as the result of making international movements harder under more restrictive security concerns), power outages like the 2003 Italy blackout, and so on motivated researchers to study and evaluate the effects of cascading failures in interdependent networked systems . The studies showed that small‐ or large‐scale failures in some critical infrastructure sectors (CISs), including cyberspace, potentially cascade and make catastrophic events . It is evident that the stability of the security and economy of nations are tightly influenced by threats to the cyberspace from different sources.…”

Section: Related Workmentioning

confidence: 99%

Security Investment in Contagious Networks

Hasheminasab

Ladani

2018

Risk Analysis

View full text Add to dashboard Cite

Security of the systems is normally interdependent in such a way that security risks of one part affect other parts and threats spread through the vulnerable links in the network. So, the risks of the systems can be mitigated through investments in the security of interconnecting links. This article takes an innovative look at the problem of security investment of nodes on their vulnerable links in a given contagious network as a game-theoretic model that can be applied to a variety of applications including information systems. In the proposed game model, each node computes its corresponding risk based on the value of its assets, vulnerabilities, and threats to determine the optimum level of security investments on its external links respecting its limited budget. Furthermore, direct and indirect nonlinear influences of a node's security investment on the risks of other nodes are considered. The existence and uniqueness of the game's Nash equilibrium in the proposed game are also proved. Further analysis of the model in a practical case revealed that taking advantage of the investment effects of other players, perfectly rational players (i.e., those who use the utility function of the proposed game model) make more cost-effective decisions than selfish nonrational or semirational players.

show abstract

Section: Related Workmentioning

confidence: 99%

Security Investment in Contagious Networks

Hasheminasab

Ladani

2018

Risk Analysis

View full text Add to dashboard Cite

show abstract

“…In reality, interdependent networks, especially those systems of interdependent networks formed by communication networks and other infrastructure networks, face many other threats, such as failure of overload [12][13][14] and epidemic spreading [15]. The interdependent relationship among networks is considered as a major issue in diffusion and spreading processes over a multilayer networks system [16,17].…”

Section: Introductionmentioning

confidence: 99%

Epidemic Spreading in Interdependent Networks

Jiang

Ouyang

et al. 2018

Mathematical Problems in Engineering

View full text Add to dashboard Cite

We introduce a dynamic process of epidemic spreading into interdependent networks because, in reality, interdependent networks are facing the threat of epidemic spreading, which still lacks research. With our model, we reveal that (i) interdependent networks are more fragile than an isolated single network when facing the threat of an epidemic; (ii) an epidemic is not massively blocked by cascading failure, even if cascading failure spreads much faster; (iii) interdependent networks are more fragile, with a larger value of average degree compared with epidemic spreading. Moreover, we propose an iterative method for estimating the fraction of removed or failed nodes in a system of interdependent networks using percolation theory. This research can improve the comprehension of interdependent networks from the point of view of epidemic spreading.

show abstract

“…Examples of such infrastructures include power grid and communication networks, where a communication network controls a power grid network and the power grid network in turn provides power to the communication network 20 . Owing to this coupling relationship they can be modeled as interdependent networks 21,22,23 . In two interdependent networks A and B, a node in network A is interdependent on its coupling node in network B when the node in network A needs the coupling node from network B to function properly, and vice versa.…”

Section: Chen Hong Et Almentioning

confidence: 99%

Cascading failures with local load redistribution in interdependent Watts–Strogatz networks

Chen

Zhang

Wei

et al. 2016

Int. J. Mod. Phys. C

Self Cite

View full text Add to dashboard Cite

Cascading failures of loads in isolated networks have been studied extensively over the last decade. Since 2010, such research has extended to interdependent networks. In this paper, we study cascading failures with local load redistribution in interdependent WattsStrogatz networks. The effects of rewiring probability and coupling strength on the resilience of interdependent Watts-Strogatz networks have been extensively investigated. It has been found that, for small values of the tolerance parameter, interdependent networks are more vulnerable as rewiring probability increases. For larger values of the tolerance parameter, the robustness of interdependent networks firstly decreases and then increases as rewiring probability increases. Coupling strength has a different impact on robustness.For low values of coupling strength the resilience of interdependent networks decreases with the increment of the coupling strength until it reaches a certain threshold value. For values of coupling strength above this threshold, the opposite effect is observed. Our results are helpful to understand and design resilient interdependent networks.

show abstract

Cascading failure of interdependent networks with different coupling preference under targeted attack

Cited by 84 publications

References 44 publications

Security Investment in Contagious Networks

Security Investment in Contagious Networks

Epidemic Spreading in Interdependent Networks

Cascading failures with local load redistribution in interdependent Watts–Strogatz networks

Contact Info

Product

Resources

About