Collaborative Research: NeTS: Medium: Large Scale Analysis of Configurations and Management Practices in the Domain Name System

合作研究：NetS：中型：域名系统配置和管理实践的大规模分析

• 批准号: 2312709
• 负责人: Paul Barford
• 金额: $ 52.5万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Standard 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=2312709&HistoricalAwards=false
• 关键词: Collaborative; Research; NeTS; Medium; Large

This project will build a broad and fundamental body of knowledge on the characteristics of configurations and management practices used in the operation of the Internet’s Domain Name System (DNS). Large public datasets will be used to analyze and statistically model the DNS contents. Graph-based analysis will be used to characterize and quantify activities performed by registrars and domain operators. Tools will be developed for the research community to support machine learning applications for the DNS, anomaly detection in the DNS, and a “DNS Workbench” enabling synthetic DNS workload generation for simulation and laboratory-based research on DNS configuration, management and performance.This project consists of two complementary components. The scientific component will focus on empirical characterization of the DNS as a whole and in parts by developing and applying techniques from graph theory, statistics and machine learning. The engineering component will use findings from the empirical analysis to identify operational practices, to inform investigation of tools and to drive new insights about how the DNS is used in practice. The project will deliver new insights about how the DNS can be improved as well as new tools for deriving and replicating those insights.This project will contribute a deeper understanding of what is usual, and what is unusual, with respect to the contents of the DNS. New techniques and findings from this project will lead to a more robust, manageable, and better performing DNS, which has potential to positively impact society as a whole. New materials for networking and data science courses will be developed based on our research. The students who work on the project will receive guidance and mentorship. Research results will be disseminated by publishing in respected academic conferences and workshops, and all software and data artifacts will be made available to the community.The project webpage will be hosted at https://macro-dns.github.io The webpage will include an overview of the project, project participants, updates on latest results and publications. It will also include all software and data artifacts developed during the project. The webpage and associated repositories will be available on github on an on-going basis after the conclusion 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.

该项目将建立关于Internet域名系统（DNS）运行中配置和管理实践特征的广泛而基本的知识体系。大型公共数据集将用于分析和统计地对DNS内容进行建模。基于图的分析将用于表征和量化注册服务商和域操作员执行的活动。将为研究社区开发工具，以支持DNS的机器学习应用程序，DNS中的异常检测以及“ DNS Workbench”，从而使合成DNS工作负载能够生成用于模拟和基于实验室的DNS配置，管理，管理和性能的研究。该项目由两个完整组成部分组成。科学组成部分将通过开发和应用图理论，统计和机器学习的技术来集中于整个DN和部分的经验表征。该工程组件将使用经验分析的发现来确定运营实践，告知工具投资，并推动有关如何在实践中使用DNS的新见解。该项目将提供有关如何改进DN的新见解，以及用于得出和复制这些见解的新工具。该项目将对DNS的内容有更深入的了解。该项目的新技术和发现将导致更强大，易于管理和更好的DNS，这有可能积极影响整个社会。将根据我们的研究开发用于网络和数据科学课程的新材料。从事该项目的学生将获得指导和心态。研究结果将通过在受人尊敬的学术会议和研讨会上发布来传播，并且所有软件和数据工件将提供给社区。项目网页将在https://macro-dns.github.io上托管。网页将包括对项目参与者的概述，项目参与者，最新结果和出版物。它还将包括项目期间开发的所有软件和数据工件。项目结束后，网页和关联的存储库将在GitHub上持续使用。该奖项反映了NSF的法定任务，并通过使用基金会的知识分子优点和更广泛的影响审查标准来评估被认为是宝贵的支持。