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Identifying critical autonomous systems in the Internet

机译:识别Internet中的关键自治系统

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The Internet not only facilitates our daily activities, such as communication, entertainment and shopping but also serves as the enabling technology for many critical services, including finance, manufacturing, healthcare and transportation. On the other hand, a wide spectrum of attacks targets its communication infrastructure to disable or disrupt the network connectivity and traffic flow until recovery processes take place. Attacking all autonomous systems (ASes) in the Internet is typically beyond the capability of an adversary. Therefore, targeting a small number of ASes which results in the highest impact is the best strategy for attackers. Similarly, it is important for network practitioners to identify, fortify and secure those critical ASes to mitigate the impact of the attacks. In this study we introduce an intuitive and effective measure, IP address spatial path stress centrality, to assess and identify the critical ASes in the Internet. We compare IP address spatial path stress centrality to the three well-known and widely used centrality measures, namely customer-cone size, node degree and betweenness. We demonstrate that the proposed measure incorporates business relations and IP address spaces to achieve a better measure for identifying the critical ASes in the Internet.
机译:互联网不仅促进了我们的日常活动,例如通讯,娱乐和购物,而且还成为许多关键服务(包括金融,制造业,医疗保健和运输)的支持技术。另一方面,各种各样的攻击针对其通信基础结构以禁用或破坏网络连接和流量,直到恢复过程发生为止。攻击Internet中的所有自治系统(ASes)通常超出了攻击者的能力。因此,针对少数AS产生最大影响的AS是攻击者的最佳策略。同样,对于网络从业人员来说,重要的是要识别,加强和保护这些关键的AS,以减轻攻击的影响。在这项研究中,我们介绍了一种直观有效的方法,即IP地址空间路径应力集中性,以评估和识别Internet中的关键AS。我们将IP地址空间路径应力集中度与三种众所周知且广泛使用的集中度度量进行比较,即客户锥体大小,节点度和中间度。我们证明了拟议的措施结合了业务关系和IP地址空间,以实现更好的措施来识别Internet中的关键AS。

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