SMap:针对欺骗的全互联网扫描

Tianxiang Dai, Haya Shulman
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引用次数: 6

摘要

为了保护自己免受攻击,网络需要执行入站过滤,即阻止从欺骗IP地址发送的入站数据包。尽管这是一种广为人知的最佳实践,但仍不清楚有多少网络不阻止欺骗数据包。在互联网规模上推断可欺骗性的程度是具有挑战性的,尽管付出了多种努力,但现有的研究目前只涵盖了有限的互联网网络:它们要么可以测量运行有错误网络堆栈实现的服务器的网络,要么需要在志愿者网络上安装测量软件,或者假设特定的属性,如跟踪路由循环。提高欺骗测量的覆盖范围至关重要。在这项工作中,我们提出了欺骗映射器(SMap):第一个用于在互联网范围内进行入侵过滤研究的扫描器。SMap利用几乎所有Internet网络中存在的标准协议来评估网络的可欺骗性。我们将SMap应用于互联网范围内的入口过滤测量:我们发现互联网中69.8%的自治系统(ase)不过滤欺骗数据包,并发现了46880个新的可欺骗的ase,这些ase在以前的研究中没有被识别出来。我们对SMap的测量提供了互联网中入口过滤部署的第一个全面视图,以及在截至2021年5月的两年内过滤欺骗数据包的补救措施。我们在https://smap.cad.sit.fraunhofer.de上设置了一个web服务,使用SMap执行持续的internet范围的数据收集,并显示来自欺骗评估的统计信息。我们将我们的数据集以及SMap(实现和源代码)公开,使研究人员能够重现和验证我们的结果,并不断跟踪过滤互联网上欺骗数据包的变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SMap: Internet-wide Scanning for Spoofing
To protect themselves from attacks, networks need to enforce ingress filtering, i.e., block inbound packets sent from spoofed IP addresses. Although this is a widely known best practice, it is still not clear how many networks do not block spoofed packets. Inferring the extent of spoofability at Internet scale is challenging and despite multiple efforts the existing studies currently cover only a limited set of the Internet networks: they can either measure networks that operate servers with faulty network-stack implementations, or require installation of the measurement software on volunteer networks, or assume specific properties, like traceroute loops. Improving coverage of the spoofing measurements is critical. In this work we present the Spoofing Mapper (SMap): the first scanner for performing Internet-wide studies of ingress filtering. SMap evaluates spoofability of networks utilising standard protocols that are present in almost any Internet network. We applied SMap for Internet-wide measurements of ingress filtering: we found that 69.8% of all the Autonomous Systems (ASes) in the Internet do not filter spoofed packets and found 46880 new spoofable ASes which were not identified in prior studies. Our measurements with SMap provide the first comprehensive view of ingress filtering deployment in the Internet as well as remediation in filtering spoofed packets over a period of two years until May 2021. We set up a web service at https://smap.cad.sit.fraunhofer.de to perform continual Internet-wide data collection with SMap and display statistics from spoofing evaluation. We make our datasets as well as the SMap (implementation and the source code) publicly available to enable researchers to reproduce and validate our results, as well as to continually keep track of changes in filtering spoofed packets in the Internet.
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