Effects of Degree Correlations in Interdependent Security: Good or Bad?
Effects of Degree Correlations in Interdependent Security: Good or Bad?
复制标题
相互依存安全中程度相关性的影响：好还是坏？
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
R. La
中科院分区：
文献类型：
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作者：
R. La
我们研究程度相关性或网络混合对相互依赖的安全性的影响。我们使用依赖图对代理之间安全的相互依赖关系进行建模，并采用群体博弈模型来捕获许多代理之间的交互，当它们具有战略性并且可以选择多种安全措施来保护自己时。整体网络安全性是通过邻居的平均风险暴露（ARE）来衡量的，它与网络中的攻击总数（预期）成正比。我们首先证明存在一个独特的人口博弈纯策略纳什均衡。然后，我们证明，随着依赖图中度数较大的智能体比度数较小的智能体看到更高的风险，整体网络安全性会恶化，因为智能体经历的 ARE 增加，网络中存在更多的攻击。最后，利用这一发现，我们证明网络混合对 ARE 的影响取决于代理可用的安全措施的（成本）有效性；如果安全措施无效，增加依赖图的匹配性会导致更高的 ARE。另一方面，如果安全措施能够有效抵御攻击造成的损害和损失，那么增加分类性就会减少代理所经历的 ARE。
We study the influence of degree correlations or network mixing on interdependent security. We model the interdependence in security among agents using a dependence graph and employ a population game model to capture the interaction among many agents when they are strategic and have various security measures they can choose to defend themselves. The overall network security is measured by what we call the average risk exposure (ARE) from neighbors, which is proportional to the total (expected) number of attacks in the network. We first show that there exists a unique pure-strategy Nash equilibrium of a population game. Then, we prove that as the agents with larger degrees in the dependence graph see higher risks than those with smaller degrees, the overall network security deteriorates in that the ARE experienced by agents increases and there are more attacks in the network. Finally, using this finding, we demonstrate that the effects of network mixing on ARE depend on the (cost) effectiveness of security measures available to agents; if the security measures are not effective, increasing assortativity of dependence graph results in higher ARE. On the other hand, if the security measures are effective at fending off the damages and losses from attacks, increasing assortativity reduces the ARE experienced by agents.