2017/12/01 by Lei Wang, Wang, Lei, Xincheng Wang +1
Biochemistry, Genetics and Molecular Biology · Physics and Astronomy · #Complex Network Analysis Techniques #Diffusion and Search Dynamics #FOS: Computer and information sciences #FOS: Physical sciences #Opinion Dynamics and Social Influence #Physics and Society (physics.soc-ph) #Social and Information Networks (cs.SI)
paper · pdf · doi:10.48550/arxiv.1712.00156
openalex publication_date 2017/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Asymmetry of in/out-degree distribution is a widespread phenomenon in real-world complex networks. This paper put forward the concept of Edge Asymmetry(EA) to quantify this feature. We designed an EA-based strategy to attack six kinds of real-world networks and found that it was able to achieve the effect as well as edge betweenness-based(EB) and better than edge degree-based(ED) and random attack strategies. In simulation, we found that the greater the network asymmetry the better the EA-based attack strategy performed. By definition, the computational complexity of EA was much lower than that of EB. Therefore, EA-based attack strategies were superior in efficiency. We verified the effect of the EA-based attack strategy with four groups of large-scale networks.