标题： 复杂模型和现实网络上的攻击策略效率 显示英文标题

标题： Efficiency of attack strategies on complex model and real-world networks

摘要： 我们研究了在针对多个复杂模型和现实网络时攻击策略的效率。 我们测试了5种攻击策略，其中3种是首次在本工作中引入的，以攻击3种模型网络（Erdos和Renyi网络、Barabasi和Albert优先连接网络以及无标度网络配置模型）和3种真实网络（Gnutella对等网络、Rovira i Virgili大学的电子邮件网络以及免疫球蛋白相互作用网络）。 节点根据攻击策略定义的重要性标准依次被移除。 我们使用最大连通分量（LCC）的大小作为网络损伤的衡量标准。 我们发现攻击策略的效率（给定LCC大小减少的情况下需要删除的节点比例）取决于网络的拓扑结构，尽管基于节点连接数和介数中心性的攻击通常是最有效的策略。 按介数中心性从高到低顺序删除节点是在针对现实网络时最有效的攻击策略。 特别是对于具有幂律度分布的网络，我们在节点的顺序删除过程中观察到最有效的策略发生了变化。 显示英文摘要

摘要： We investigated the efficiency of attack strategies to network nodes when targeting several complex model and real-world networks. We tested 5 attack strategies, 3 of which were introduced in this work for the first time, to attack 3 model (Erdos and Renyi, Barabasi and Albert preferential attachment network, and scale-free network configuration models) and 3 real networks (Gnutella peer-to-peer network, email network of the University of Rovira i Virgili, and immunoglobulin interaction network). Nodes were removed sequentially according to the importance criterion defined by the attack strategy. We used the size of the largest connected component (LCC) as a measure of network damage. We found that the efficiency of attack strategies (fraction of nodes to be deleted for a given reduction of LCC size) depends on the topology of the network, although attacks based on the number of connections of a node and betweenness centrality were often the most efficient strategies. Sequential deletion of nodes in decreasing order of betweenness centrality was the most efficient attack strategy when targeting real-world networks. In particular for networks with power-law degree distribution, we observed that most efficient strategy change during the sequential removal of nodes.