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Computational complexity of network vulnerability analysis

Computational complexity of network vulnerability analysis AbstractResidual closeness is recently proposed as a vulnerability measure to characterize the stability of complex networks. Residual closeness is essential in the analysis of complex networks, but costly to compute. Currently, the fastest known algorithms run in polynomial time. Motivated by the fast-growing need to compute vulnerability measures on complex networks, new algorithms for computing node and edge residual closeness are introduced in this paper. Those proposed algorithms reduce the running times to Θ(n3) and Θ (n4) on unweighted networks, respectively, where n is the number of nodes. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Acta Universitatis Sapientiae Informatica de Gruyter

Computational complexity of network vulnerability analysis

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Publisher
de Gruyter
Copyright
© 2022 Murat Erşen Berberler, published by Sciendo
eISSN
2066-7760
DOI
10.2478/ausi-2022-0012
Publisher site
See Article on Publisher Site

Abstract

AbstractResidual closeness is recently proposed as a vulnerability measure to characterize the stability of complex networks. Residual closeness is essential in the analysis of complex networks, but costly to compute. Currently, the fastest known algorithms run in polynomial time. Motivated by the fast-growing need to compute vulnerability measures on complex networks, new algorithms for computing node and edge residual closeness are introduced in this paper. Those proposed algorithms reduce the running times to Θ(n3) and Θ (n4) on unweighted networks, respectively, where n is the number of nodes.

Journal

Acta Universitatis Sapientiae Informaticade Gruyter

Published: Dec 1, 2022

Keywords: Vulnerability; complex networks; design of algorithms; graph algorithms; 05C40; 68M10; 68R10

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