IMR: MM-1C: Methods and Metrics for IPv6 Internet Scanning

IMR：MM-1C：IPv6 互联网扫描的方法和指标

• 批准号: 2319315
• 负责人: Paul Pearce
• 金额: $ 54.98万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2026-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2319315&HistoricalAwards=false
• 关键词: IMR; MM; 1C; Methods; Metrics

Technology to quickly map (i.e., scan) the Internet and explore its characteristics is of the utmost importance to researchers, governments, policy makers and businesses. Existing technologies rely on exhaustively enumerating the entire Internet address space. With the advent and recent widespread adoption of a newer Internet addressing scheme (called IPv6), such exhaustive enumeration is impossible, preventing our existing technology from being applied to future Internet growth. This project will create new Internet mapping technologies that are suitable for the newer IPv6 addressing scheme through the careful exploration of how IPv6 is deployed in practice, the development and evaluation of key mapping metrics, and the use of reinforcement learning on known addresses.This project will enable the next generation of generative IPv6 Internet scanning, and provide a platform for extending existing IPv4 research to the IPv6 realm. Developing IPv6 scanning metrics and methods requires understanding detailed behaviors of the IPv6 protocol, service providers, address allocation, and machine-learning methods. The project will first construct a set of comprehensive metrics for understanding IPv6 scanning performance that can serve as a benchmark for evaluating current and future scanning techniques. Next the project will characterize the substantial impact of large-scale IPv6 aliasing on IPv6 scanning, and the inadequacy of prior solutions, especially in the context of existing metrics and methods. From this the project will develop an online IPv6 dealiasing strategy and evaluate it over existing methods, quantifying its improvement on IPv6 Internet scanning. Lastly, guided by the aforementioned metrics and understanding of aliasing, the project will develop a new generalized online approach to IPv6 address generation and scanning via levering reinforcement learning from a set of known seed addresses to generate a diverse set of candidate IPv6 addresses which it subsequently scans.Extending whole-Internet scanning to IPv6 is critical to a range of networking topics, from censorship measurement to network outages to vulnerability detection. Further, it is necessary to ensure results do not bias against certain regions without significant IPv4 infrastructure. Thus the value of IPv6 measurement and Internet scanning as a whole is key to researchers, policymakers, and governments. This project will produce the foundation for supporting a wide range of IPv6 Internet measurement research in the future. More information about the project, including all research papers, datasets, code, repositories, tools, results, and outreach activities can be found on the project's website: https://cc.gatech.edu/~pearce/imr_metrics_methods_ipv6/. The website will be maintained for a period of at least 5 years after completion of the project.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

快速绘制(即扫描)互联网地图并探索其特征的技术对研究人员、政府、政策制定者和企业至关重要。现有技术依赖于详尽地列举整个互联网地址空间。随着较新的互联网寻址方案(称为IPv6)的出现和最近的广泛采用，这种详尽的列举是不可能的，从而阻止了我们现有的技术应用于未来的互联网增长。该项目将通过仔细探索IPv6如何在实践中部署、关键映射指标的开发和评估以及在已知地址上使用强化学习来创建适用于较新的IPv6寻址方案的新的互联网映射技术。该项目将使下一代生成的IPv6互联网扫描成为可能，并为将现有的IPv4研究扩展到IPv6领域提供一个平台。开发IPv6扫描指标和方法需要了解IPv6协议、服务提供商、地址分配和机器学习方法的详细行为。该项目将首先构建一套全面的指标来了解IPv6扫描性能，这些指标可以作为评估当前和未来扫描技术的基准。接下来，该项目将描述大规模IPv6混叠对IPv6扫描的重大影响，以及先前解决方案的不足，特别是在现有指标和方法的背景下。该项目将开发一种在线IPv6去别名策略，并将其与现有方法进行评估，量化其在IPv6互联网扫描方面的改进。最后，在上述指标和对混叠的理解的指导下，该项目将开发一种新的通用在线方法来生成和扫描IPv6地址，方法是利用从一组已知种子地址中的强化学习来生成一组不同的候选IPv6地址，然后进行扫描。将全互联网扫描扩展到IPv6对于从审查测量到网络中断再到漏洞检测等一系列网络主题至关重要。此外，有必要确保结果不会对没有重要的IPv4基础设施的某些地区产生偏见。因此，IPv6测量和互联网扫描的整体价值对研究人员、政策制定者和政府来说是关键。该项目将为未来支持广泛的IPv6互联网测量研究奠定基础。有关该项目的更多信息，包括所有研究论文、数据集、代码、存储库、工具、结果和推广活动，可在该项目的网站上找到：https://cc.gatech.edu/~pearce/imr_metrics_methods_ipv6/.该网站将在项目完成后保持至少5年的时间。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。