Edge attack strategies in interdependent scale-free networks
Yucheng Hao,
Limin Jia and
Yanhui Wang
Physica A: Statistical Mechanics and its Applications, 2020, vol. 540, issue C
Abstract:
In existing works, the interdependent network reflects the great vulnerability and the study on its robustness is limited to attacks on nodes. Based on the characteristics of the node and interdependent networks, we propose fourteen edge attack strategies by two edge importance functions. Then, interdependent BA networks with assortative coupling(AC), disassortative coupling(DC), and random coupling(RC) are constructed, whose robustness is quantified by the relative size of the giant component under varying a fraction f of removed edges. It is found that in terms of the edge importance function concerning the sum of the information between networks under AC and RC, attack strategies with the harmonic closeness (SH) and the degree (SD) are the most harmful for smaller and bigger f, respectively; Under DC, SH is the most efficient. In terms of the edge importance function concerning the product of the information between networks, the efficiency of the attack strategy with the degree (PD) is the highest under AC with bigger f, DC and RC. Through the comparison of different attack strategies, the results demonstrate that attack strategies with the product of the information between networks are more efficient than the ones with the sum of the information between networks under DC and RC. Furthermore, we find that interdependent BA networks with DC are more vulnerable while the ones with AC are more robust under different edge attack strategies.
Keywords: Interdependent networks; Edge attack strategy; Centrality measure; Robustness; Cascading failure (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (5)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:540:y:2020:i:c:s0378437119315687
DOI: 10.1016/j.physa.2019.122759
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