Clusters in the Expanse:
Understanding and Unbiasing IPv6 Hitlists
Oliver Gasser, Quirin Scheitle, Paweł Foremski, Qasim Lone,
Maciej Korczyński, Stephen D. Strowes, Luuk Hendriks, Georg Carle
Abstract. Network measurements are an important tool in understanding the Internet. Due
to the expanse of the IPv6 address space, exhaustive scans as in IPv4 are not possible for IPv6.
In recent years, several studies proposed to use target lists of IPv6 addresses, called
In this paper, we show that addresses in IPv6 hitlists are heavily clustered. We present novel
techniques that allow to push IPv6 hitlists from quantity to quality. We perform a longitudinal
active measurement study over 6 months, targeting more than 50 M addresses. We develop a
rigorous method to detect aliased prefixes, which identifies 1.5 % of our prefixes as aliased,
pertaining to about half of our target addresses. Using entropy clustering, we group the entire
hitlist into just 6 distinct addressing schemes. Furthermore, we perform client measurements by
To encourage reproducibility in network measurement research and serve as a starting point for
future IPv6 studies, we publish source code, analysis tools, and data.
Pre-print. Read the pre-print of our paper at arXiv.org:
On this website we publish additional entropy clustering and zesplot figures for in-depth analysis.
We plan to publish data, source code, and analysis tool of the work on IPv6 hitlists.
We provide additional in-depth plots accompanying the analyses in our paper.