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A invulnerability assessment based on importance-degree of node for weighted network under attack with partial information

机译:基于攻击局部信息的加权网络的重要性基于节点的重要性评估

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We study invulnerability of complex networks subject to attacks on nodes and links. For the purpose of precisely assessing invulnerability of complex networks, in this paper we proposed an invulnerability assessment on the basis of importance-degree and partial attack information by measuring two metrics of network invulnerability, robustness and efficiency. We defined the term of importance-degree to describe importance of different nodes in the networks. We form a probability model to describe the process of acquiring information under three types of attacks, random attacks, partial information attacks and intentional attacks, and simulate the process of acquiring partial information by sampling nodes in accordance with the probability model. The simulation results contain that weighted networks hold strong invulnerability to random attacks, whereas they are extremely fragile when suffering those intentional attacks; more information is exposed, less invulnerability networks display, especially complete information attacks which are the same with intentional attacks that all information of nodes or links would be acquired by assailants; the more important information is acquired, the more quickly network invulnerability decreases. This conclusion can guide people to implement corresponding protection strategy of hiding important information based on the importance-degree of nodes.
机译:我们研究复杂网络的无懈可击,受节点和链接的攻击。为了精确评估复杂网络的无漏能性,在本文中,我们通过测量网络免疫性,鲁棒性和效率的两个指标,提出了一种重要性和部分攻击信息的无情评估。我们定义了重要性 - 描述网络中不同节点的重要性。我们形成概率模型来描述根据三种类型的攻击,随机攻击,部分信息攻击和故意攻击获取信息的过程,并根据概率模型来模拟采样节点获取部分信息的过程。仿真结果包含加权网络对随机攻击的强大无懈可击性,而在遭受这些故意攻击时它们非常脆弱;更详细的信息是暴露的,较少的禁用网络显示,尤其是完整的信息攻击,与故意攻击相同,即攻击者将获得所有节点或链接的所有信息;获取更重要的信息,网络禁止率越快减少。这一结论可以指导人们根据节点重要性程度来实施隐藏重要信息的相应保护策略。

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