Vulnerability Analysis of Complex Network Important Nodes Based on Multi-attribute

Jintao Yu, B. Xiao, Hao Li
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Abstract

∗ In order to predict the fragile nodes in complex networks more accurately, an important node mining method on the basis of multi-attributes is presented in the article. This method is suitable for both directed and undirected simple graph with no self-loops. The experiments based on ARPA-Net data show that the proposed method has better predictive ability on finding important nodes which can be applied to vulnerability analysis of complex network.
基于多属性的复杂网络重要节点脆弱性分析
*为了更准确地预测复杂网络中的脆弱节点,本文提出了一种基于多属性的重要节点挖掘方法。该方法适用于无自环的有向和无向简单图。基于ARPA-Net数据的实验表明,该方法在寻找重要节点方面具有较好的预测能力,可应用于复杂网络的漏洞分析。
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