A comprehensive characterization of DNS data

Abstract

The Domain Name System (DNS) is responsible for translating human-readable names into computer-friendly identifiers and employs a reverse tree architecture to facilitate this translation. The forward DNS (fDNS) translates human-readable domain names into computer values, while the reverse DNS (rDNS) usually maps an IP address to a hostname. The DNS has evolved into a more intricate system, driven by economic incentives, with data stewardship being delegated to numerous autonomous stakeholders. Due to its role in Internet infrastructure, studying DNS is fundamental for both practical and security reasons. In this work, we characterize commonly used DNS datasets and the challenges linked to their usage. We thoroughly survey DNS focused research studies published over the course of more than a decade, within more than 15 proceedings, and observe a prominent reliance (62%) on short-term datasets. Our investigation into the challenges that limit the adoption of long-term datasets reveals that some of these challenges are associated with the distributed design of the DNS, while others are associated with the evolution of the DNS deployment. That is, we found that, the diversity of stakeholders has the potential to impede data collection and access by various stakeholders, as well as the sharing of data between operators and researchers. Specifically, the distributed design of the DNS leads to challenges regarding namespace coverage, privacy, confidentiality, format, size, and time granularity. Furthermore, certain DNS data is considered commercially sensitive, which further increases the penumbra over the global DNS exchanges, leading to a lack of publicly available DNS data. In earlier works, we observe a distinction in research topics between studies using actively and passively collected DNS data, followed by a recent convergence in topics investigated across both data collection approaches. Lastly, we noted that rDNS data is studied much less than fDNS, i.e., only 2.7% of the studied papers.