Challenges in inferring spoofed traffic at IXPs
Challenges in inferring spoofed traffic at IXPs
复制标题
推断 IXP 欺骗流量的挑战
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
M. Barcellos
中科院分区：
文献类型：
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作者：
L. F. Müller;M. Luckie;B. Huffaker;K. Claffy;M. Barcellos
确定网络将转发欺骗流量通常需要在该网络中进行主动探测，从而有效地阻止对这种全球互联网漏洞的全面了解。最近，研究人员提出使用互联网交换点（IXP）作为观测站来检测欺骗数据包，通过利用从边界网关协议（BGP）数据中提取的自治系统（AS）拓扑知识来推断哪些源地址应该合法地出现在IXP交换结构的各个部分。我们证明，现有的文献没有捕捉到这种方法的几个基本挑战，包括BGP数据源中的噪声，启发式AS关系推断，和IXP互连结构的特质。我们提出了一种新的方法来应对这些挑战，利用客户锥语义的AS关系，指导域间流量的精确分类锥内，锥外（欺骗），无法验证，bogon，和未分配。我们将我们的方法应用到一个中等规模的IXP，约200名成员，并找到一个上限体积的锥外交通是一个数量级以上，比以前的方法推断相同的数据。我们的工作说明了对互联网基础设施进行科学评估的微妙之处，以及社区关注复制和重复以前方法的必要性。
Ascertaining that a network will forward spoofed traffic usually requires an active probing vantage point in that network, effectively preventing a comprehensive view of this global Internet vulnerability. Recently, researchers have proposed using Internet Exchange Points (IXPs) as observatories to detect spoofed packets, by leveraging Autonomous System (AS) topology knowledge extracted from Border Gateway Protocol (BGP) data to infer which source addresses should legitimately appear across parts of the IXP switch fabric. We demonstrate that the existing literature does not capture several fundamental challenges to this approach, including noise in BGP data sources, heuristic AS relationship inference, and idiosyncrasies in IXP interconnectivity fabrics. We propose a novel method to navigate these challenges, leveraging customer cone semantics of AS relationships to guide precise classification of inter-domain traffic as in-cone, out-of-cone (spoofed), unverifiable, bogon, and unassigned. We apply our method to a mid-size IXP with approximately 200 members, and find an upper bound volume of out-of-cone traffic to be more than an order of magnitude less than the previous method inferred on the same data. Our work illustrates the subtleties of scientific assessments of operational Internet infrastructure, and the need for a community focus on reproducing and repeating previous methods.
Dagstuhl 实验网络研究再现性初学者指南
影响因子：
2.8
作者：
Bajpai, Vaibhav;Brunstrom, Anna;Feldmann, Anja;Kellerer, Wolfgang;Pras, Aiko;Schulzrinne, Henning;Smaragdakis, Georgios;Wählisch, Matthias;Wehrle, Klaus
通讯作者：
Wehrle, Klaus