TY - GEN
T1 - Prefix Top Lists Reloaded
T2 - A Temporal Prefix Ranking Dataset
AU - Kastanakis, Savvas
AU - Fontein, Rick
AU - Khadka, Shyam Krishna
AU - Jaw, Ebrima
AU - Hesselman, Cristian
AU - Jonker, Mattijs
N1 - © 2026 The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2026
Y1 - 2026
N2 - Accurate Internet measurements depend on well-defined targets. A popular mechanism for target selection is domain-based top lists, e.g., the Tranco or Cisco Umbrella lists. Such lists have a few shortcomings such as the lack of aggregation across related domain names and high volatility over time. Prefix Top Lists (PTL) were introduced in 2019 to address these issues, by aggregating domain names into IP prefixes and applying a Zipf-based ranking model to improve stability and representativeness, nonetheless, the original PTL resource was discontinued, leaving a gap in publicly available prefix-level data. In this replication study, we revive and enhance the PTL resource by incorporating a broader range of domain-based top lists. Our approach involves mapping domain names to IP prefixes using DNS resolution and BGP routing data, ranking prefixes through a Zipf-based weighting system, and conducting three use-case studies to promote the applicability of PTLs. We release the complete PTL toolchain as open-source software and publish weekly PTL snapshots under https://openintel.nl/data/prefix-top-lists, ensuring sustained, versioned and publicly accessible prefix-level rankings for the measurement community.
AB - Accurate Internet measurements depend on well-defined targets. A popular mechanism for target selection is domain-based top lists, e.g., the Tranco or Cisco Umbrella lists. Such lists have a few shortcomings such as the lack of aggregation across related domain names and high volatility over time. Prefix Top Lists (PTL) were introduced in 2019 to address these issues, by aggregating domain names into IP prefixes and applying a Zipf-based ranking model to improve stability and representativeness, nonetheless, the original PTL resource was discontinued, leaving a gap in publicly available prefix-level data. In this replication study, we revive and enhance the PTL resource by incorporating a broader range of domain-based top lists. Our approach involves mapping domain names to IP prefixes using DNS resolution and BGP routing data, ranking prefixes through a Zipf-based weighting system, and conducting three use-case studies to promote the applicability of PTLs. We release the complete PTL toolchain as open-source software and publish weekly PTL snapshots under https://openintel.nl/data/prefix-top-lists, ensuring sustained, versioned and publicly accessible prefix-level rankings for the measurement community.
KW - 2026 OA procedure
UR - https://www.scopus.com/pages/publications/105035322341
U2 - 10.1007/978-3-032-18268-5_1
DO - 10.1007/978-3-032-18268-5_1
M3 - Conference contribution
SN - 978-3-032-18267-8
T3 - Lecture Notes in Computer Science
SP - 3
EP - 16
BT - Passive and Active Measurement
A2 - Ferlin-Reiter, Simone
A2 - Fontugne, Romain
A2 - Ullrich, Johanna
PB - Springer
CY - Cham
ER -