Physics – Condensed Matter – Disordered Systems and Neural Networks
Scientific paper
2003-01-08
Phys. Rev. E 66, 065102 (2002)
Physics
Condensed Matter
Disordered Systems and Neural Networks
4 pages, 4 figures, Revtex
Scientific paper
10.1103/PhysRevE.66.065102
We live in a modern world supported by large, complex networks. Examples range from financial markets to communication and transportation systems. In many realistic situations the flow of physical quantities in the network, as characterized by the loads on nodes, is important. We show that for such networks where loads can redistribute among the nodes, intentional attacks can lead to a cascade of overload failures, which can in turn cause the entire or a substantial part of the network to collapse. This is relevant for real-world networks that possess a highly heterogeneous distribution of loads, such as the Internet and power grids. We demonstrate that the heterogeneity of these networks makes them particularly vulnerable to attacks in that a large-scale cascade may be triggered by disabling a single key node. This brings obvious concerns on the security of such systems.
Lai Ying-Cheng
Motter Adilson E.
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