NSF Award
2312711
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.<br/><br/>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.<br/><br/>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.<br/><br/>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.<br/><br/>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.
