Back-to-the-Future Whois: An IP Address Attribution Service for Working with Historic Datasets

Florian Streibelt; Martina Lindorfer; Seda Gürses; Carlos H. Gañán; Tobias Fiebig

doi:10.1007/978-3-031-28486-1_10

Back-to-the-Future Whois: An IP Address Attribution Service for Working with Historic Datasets

Florian Streibelt, Martina Lindorfer, Seda Gürses, Carlos H. Gañán, Tobias Fiebig^*

^*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

3 Citations (Scopus)

74 Downloads (Pure)

Abstract

Researchers and practitioners often face the issue of having to attribute an IP address to an organization. For current data this is comparably easy, using services like whois or other databases. Similarly, for historic data, several entities like the RIPE NCC provide websites that provide access to historic records. For large-scale network measurement work, though, researchers often have to attribute millions of addresses. For current data, Team Cymru provides a bulk whois service which allows bulk address attribution. However, at the time of writing, there is no service available that allows historic bulk attribution of IP addresses. Hence, in this paper, we introduce and evaluate our ‘Back-to-the-Future whois’ service, allowing historic bulk attribution of IP addresses on a daily granularity based on CAIDA Routeviews aggregates. We provide this service to the community for free, and also share our implementation so researchers can run instances themselves.

Original language	English
Title of host publication	Passive and Active Measurement - 24th International Conference, PAM 2023, Proceedings
Editors	Anna Brunstrom, Marcel Flores, Marco Fiore
Publisher	Springer
Pages	209-226
Number of pages	18
ISBN (Print)	9783031284854
DOIs	https://doi.org/10.1007/978-3-031-28486-1_10
Publication status	Published - 2023
Event	24th International Conference on Passive and Active Measurement, PAM 2023 - Virtual, Online Duration: 21 Mar 2023 → 23 Mar 2023

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13882 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	24th International Conference on Passive and Active Measurement, PAM 2023
City	Virtual, Online
Period	21/03/23 → 23/03/23

Access to Document

10.1007/978-3-031-28486-1_10

978-3-031-28486-1_10Final published version, 2.52 MBLicence: CC BY

Cite this

Streibelt, F., Lindorfer, M., Gürses, S., Gañán, C. H., & Fiebig, T. (2023). Back-to-the-Future Whois: An IP Address Attribution Service for Working with Historic Datasets. In A. Brunstrom, M. Flores, & M. Fiore (Eds.), Passive and Active Measurement - 24th International Conference, PAM 2023, Proceedings (pp. 209-226). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13882 LNCS). Springer. https://doi.org/10.1007/978-3-031-28486-1_10

Streibelt, Florian ; Lindorfer, Martina ; Gürses, Seda et al. / Back-to-the-Future Whois : An IP Address Attribution Service for Working with Historic Datasets. Passive and Active Measurement - 24th International Conference, PAM 2023, Proceedings. editor / Anna Brunstrom ; Marcel Flores ; Marco Fiore. Springer, 2023. pp. 209-226 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Back-to-the-Future Whois: An IP Address Attribution Service for Working with Historic Datasets",

abstract = "Researchers and practitioners often face the issue of having to attribute an IP address to an organization. For current data this is comparably easy, using services like whois or other databases. Similarly, for historic data, several entities like the RIPE NCC provide websites that provide access to historic records. For large-scale network measurement work, though, researchers often have to attribute millions of addresses. For current data, Team Cymru provides a bulk whois service which allows bulk address attribution. However, at the time of writing, there is no service available that allows historic bulk attribution of IP addresses. Hence, in this paper, we introduce and evaluate our {\textquoteleft}Back-to-the-Future whois{\textquoteright} service, allowing historic bulk attribution of IP addresses on a daily granularity based on CAIDA Routeviews aggregates. We provide this service to the community for free, and also share our implementation so researchers can run instances themselves.",

author = "Florian Streibelt and Martina Lindorfer and Seda G{\"u}rses and Ga{\~n}{\'a}n, {Carlos H.} and Tobias Fiebig",

year = "2023",

doi = "10.1007/978-3-031-28486-1_10",

language = "English",

isbn = "9783031284854",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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pages = "209--226",

editor = "Anna Brunstrom and Marcel Flores and Marco Fiore",

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Streibelt, F, Lindorfer, M, Gürses, S , Gañán, CH & Fiebig, T 2023, Back-to-the-Future Whois: An IP Address Attribution Service for Working with Historic Datasets. in A Brunstrom, M Flores & M Fiore (eds), Passive and Active Measurement - 24th International Conference, PAM 2023, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13882 LNCS, Springer, pp. 209-226, 24th International Conference on Passive and Active Measurement, PAM 2023, Virtual, Online, 21/03/23. https://doi.org/10.1007/978-3-031-28486-1_10

Back-to-the-Future Whois: An IP Address Attribution Service for Working with Historic Datasets. / Streibelt, Florian; Lindorfer, Martina; Gürses, Seda et al.
Passive and Active Measurement - 24th International Conference, PAM 2023, Proceedings. ed. / Anna Brunstrom; Marcel Flores; Marco Fiore. Springer, 2023. p. 209-226 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13882 LNCS).

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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T2 - 24th International Conference on Passive and Active Measurement, PAM 2023

AU - Streibelt, Florian

AU - Lindorfer, Martina

AU - Gürses, Seda

AU - Gañán, Carlos H.

AU - Fiebig, Tobias

PY - 2023

Y1 - 2023

N2 - Researchers and practitioners often face the issue of having to attribute an IP address to an organization. For current data this is comparably easy, using services like whois or other databases. Similarly, for historic data, several entities like the RIPE NCC provide websites that provide access to historic records. For large-scale network measurement work, though, researchers often have to attribute millions of addresses. For current data, Team Cymru provides a bulk whois service which allows bulk address attribution. However, at the time of writing, there is no service available that allows historic bulk attribution of IP addresses. Hence, in this paper, we introduce and evaluate our ‘Back-to-the-Future whois’ service, allowing historic bulk attribution of IP addresses on a daily granularity based on CAIDA Routeviews aggregates. We provide this service to the community for free, and also share our implementation so researchers can run instances themselves.

AB - Researchers and practitioners often face the issue of having to attribute an IP address to an organization. For current data this is comparably easy, using services like whois or other databases. Similarly, for historic data, several entities like the RIPE NCC provide websites that provide access to historic records. For large-scale network measurement work, though, researchers often have to attribute millions of addresses. For current data, Team Cymru provides a bulk whois service which allows bulk address attribution. However, at the time of writing, there is no service available that allows historic bulk attribution of IP addresses. Hence, in this paper, we introduce and evaluate our ‘Back-to-the-Future whois’ service, allowing historic bulk attribution of IP addresses on a daily granularity based on CAIDA Routeviews aggregates. We provide this service to the community for free, and also share our implementation so researchers can run instances themselves.

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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ER -

Streibelt F, Lindorfer M, Gürses S , Gañán CH, Fiebig T. Back-to-the-Future Whois: An IP Address Attribution Service for Working with Historic Datasets. In Brunstrom A, Flores M, Fiore M, editors, Passive and Active Measurement - 24th International Conference, PAM 2023, Proceedings. Springer. 2023. p. 209-226. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-28486-1_10

Back-to-the-Future Whois: An IP Address Attribution Service for Working with Historic Datasets

Abstract

Publication series

Conference

Access to Document

Other files and links

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Cybersecurity (TPM)

Cite this

Back-to-the-Future Whois: An IP Address Attribution Service for Working with Historic Datasets

Abstract

Publication series

Conference

Access to Document

Other files and links

Fingerprint

Projects

Cybersecurity (TPM)

Cite this