Cascade control and defense in complex networks.

By Adilson E. Motter. Physical Review Letters, 2004

655 citations recorded by the source corpus.

Complex networks with a heterogeneous distribution of loads may undergo a global cascade of overload failures when highly loaded nodes or edges are removed due to attacks or failures. Since a small attack or failure has the potential to trigger a global cascade, a fundamental question regards the possible strategies of defense to prevent the cascade from propagating through the entire network. Here we introduce and investigate a costless strategy of defense based on a selective further removal of nodes and edges, right after the initial attack or failure. This intentional removal of network elements is shown to drastically reduce the size of the cascade.

Subfields: Computer Networks and Communications, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/1bc47140e2f67f8c1e2ab6268c618037d8b54c8c

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In Computer Networks and Communications

In Statistical and Nonlinear Physics

Citations in the corpus

Cascade-based attack vulnerability on the US power grid. (2009, background): “In addition, a number of aspects of cascading failures have been discussed in some literatures, including the cascade control and defense strategy (Zhao and Gao, 2007; Sun et al., 2008; Motter, 2004; Wang and Kim, 2007; Ash and Newth, 2007), the model for describing cascade phenomena (Bao et al.”
Critical phenomena in complex networks (2007, background): “This model can be easily generalized: α may be defined as a random variable, instead of betweenness centrality other characteristics may be used, etc.—see, e.g., Motter (2004) or, for a model with overloaded links, Moreno et al. (2003) and Bakke et al. (2006).”
Robustness and resilience of complex networks (2024, positive): “An emblematic example is the unfolding of a cascade of failures caused by perturbations localized on nodes that are central for information exchange (such as signalling, electricity redistribution and so on) between the units of a system 30,31 .”
Modelling interdependent infrastructures using interacting dynamical models (2008, background): “These models have shown the way complex networks react to faults or attacks; their behaviour often results in a dramatic cascade phenomenon (Motter and Lai, 2002; Motter, 2004).”
Vital nodes identification in complex networks (2016, background): “Empirical results on real-world networks show that the data from the Internet community, such as email network, usually have high bipartivity, while the collaboration networks have relative lower values [296].”