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Mathematical Problems in Engineering
Volume 2013, Article ID 938398, 10 pages
Research Article

Identifying Vulnerable Nodes of Complex Networks in Cascading Failures Induced by Node-Based Attacks

1College of Mathematics and Information Science, Shandong Institute of Business and Technology, Shandong, Yantai 264005, China
2School of Computer Science, National University of Defense Technology, Hunan, Changsha 410073, China
3Information Security Center, Beijing University of Posts and Telecommunications, P.O. Box 145, Beijing 100876, China
4National Computer Network Emergency Response Technical Team/Coordination Center, Beijing 100029, China

Received 18 July 2013; Accepted 7 August 2013

Academic Editor: Ming Li

Copyright © 2013 Shudong Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


In the research on network security, distinguishing the vulnerable components of networks is very important for protecting infrastructures systems. Here, we probe how to identify the vulnerable nodes of complex networks in cascading failures, which was ignored before. Concerned with random attack (RA) and highest load attack (HL) on nodes, we model cascading dynamics of complex networks. Then, we introduce four kinds of weighting methods to characterize the nodes of networks including Barabási-Albert scale-free networks (SF), Watts-Strogatz small-world networks (WS), Erdos-Renyi random networks (ER), and two real-world networks. The simulations show that, for SF networks under HL attack, the nodes with small value of the fourth kind of weight are the most vulnerable and the ones with small value of the third weight are also vulnerable. Also, the real-world autonomous system with power-law distribution verifies these findings. Moreover, for WS and ER networks under both RA and HL attack, when the nodes have low tolerant ability, the ones with small value of the fourth kind of weight are more vulnerable and also the ones with high degree are easier to break down. The results give us important theoretical basis for digging the potential safety loophole and making protection strategy.