What's in the Dataset? Unboxing the APNIC per AS User Population Dataset

Loqman Salamatian, Calvin Ardi, Vasileios Giotsas, Matt Calder, Ethan Katz-Bassett, Todd Arnold

Abstract: The research measurement community needs methods and datasets to identify user concentrations and to accurately weight ASes against each other for analyzing measurements' coverage. However, academic researchers traditionally lack visibility into how many users are in each network or how much traffic flows to each network and so often fall back on treating all IP addresses or networks equally. As an alternative, some recent studies have used the APNIC per AS Population Estimates dataset, but it is unvalidated and its methodology is not fully public.In this work, we validate its use as a fairly reliable user population indicator. Our approach includes a detailed comparative analysis using a global CDN dataset, providing concrete evidence of the APNIC dataset's accuracy. We find that the APNIC per-AS user estimates closely align with the Content Delivery Network (CDN) per-AS user estimates in 51.2% of countries and correctly identify the largest networks in 93.9% of cases. When we investigate the agreement with CDN traffic volume, the APNIC dataset closely aligns in 36.5% of countries, increasing to 91.0% when focusing only on larger networks. We also evaluate the limitations of the APNIC dataset, particularly its inability to accurately identify user populations for ASes in certain countries. To address this, we introduce new methods to improve its usability by focusing on the statistical representativeness of the underlying data collection process and ensuring consistency across several public datasets.