A critical point for random graphs with a given degree sequence
Random Graphs 93 Proceedings of the sixth international seminar on Random graphs and probabilistic methods in combinatorics and computer science
On power-law relationships of the Internet topology
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Edge vulnerability in neural and metabolic networks
Biological Cybernetics
Computers and Operations Research
On approximation of new optimization methods for assessing network vulnerability
INFOCOM'10 Proceedings of the 29th conference on Information communications
On the discovery of critical links and nodes for assessing network vulnerability
IEEE/ACM Transactions on Networking (TON)
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Many complex networks are discovered to follow the powerlaw distribution in degree sequence, ranging from the Internet, WWW to social networks. Unfortunately, there exist a great number of threats to these complex systems. In this context, it is crucial to understand the behaviors of power-law networks under various threats. Although power-law networks have been found robust under random failures but vulnerable to intentional attacks by experimental observations, it remains hard to theoretically assess their robustness so as to design a more stable complex network. In this paper, we assess the vulnerability of power-law networks with respect to their global pairwise connectivity, i.e. the number of connected node-pairs, where a pair of nodes are connected when there is a functional path between them. According to our in-depth probabilistic analysis under the theory of random power-law graph model, our results illustrate the best range of exponential factors in which the power-law networks are almost surely unaffected by any random failures and less likely to be destructed under adversarial attacks.