CORRELATION ANALYSIS OF ATTACK STRATEGIESAND ROBUSTNESS ANALYSIS ON THREE NETWORK MODELS

Network centrality metrics based on heuristics which work as a guideline onremoving vertices is a vital topic for the research of network robustness. In this paper,we analyze the correlation and difference between 12 popular centrality metrics amongthree distinct network models, including the correlation analysis and granularity anal-ysis. We also concern about the destructiveness of these centrality metrics when theyare used as attack strategies. The results show that most of the centrality metrics arehighly correlated with each other across three network models. The granularity analysison centrality metrics is also considered in this paper. The experiment results also ver-ify the previous conclusion that scale free networks are more vulnerable to intentionalattack than other networks. We observe that more correlated centrality metrics wouldcause more similar damage to network connectivity; at the meantime, we also find thatthe attack strategies based on few centrality metrics could destroy networks very quickly.All these results inspire us that there is a paradigm that could detect the attack strategywith strong destructiveness for distinct networks by combining the highly correlated andhighly destructive metrics