Clusters in the expanse: Understanding and unbiasing IPv6 Hitlists

Oliver Gasser, Qasim Lone, Quirin Scheitle, Maciej Korczyński, Pawel Foremski, Stephen D. Strowes, Luuk Hendriks, Georg Carle

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    6 Citations (Scopus)
    15 Downloads (Pure)

    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 have proposed the use of target lists of IPv6 addresses, called IPv6 hitlists. In this paper, we show that addresses in IPv6 hitlists are heavily clustered. We present novel techniques that allow IPv6 hitlists to be pushed 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 leveraging crowdsourcing. To encourage reproducibility in network measurement research and to serve as a starting point for future IPv6 studies, we publish source code, analysis tools, and data.

    Original languageEnglish
    Title of host publicationIMC 2018 - Proceedings of the Internet Measurement Conference
    PublisherAssociation for Computing Machinery (ACM)
    Pages364-378
    Number of pages15
    ISBN (Electronic)9781450356190
    DOIs
    Publication statusPublished - 31 Oct 2018
    Event18th ACM Internet Measurement Conference 2018 - Northeastern University, Boston, United States
    Duration: 31 Oct 20182 Nov 2018
    Conference number: 18
    https://conferences.sigcomm.org/imc/2018/

    Conference

    Conference18th ACM Internet Measurement Conference 2018
    Abbreviated titleACM IMC 2018
    CountryUnited States
    CityBoston
    Period31/10/182/11/18
    Internet address

    Fingerprint

    Entropy
    Internet

    Keywords

    • Aliasing
    • Clustering
    • Entropy
    • Hitlist
    • IPv6

    Cite this

    Gasser, O., Lone, Q., Scheitle, Q., Korczyński, M., Foremski, P., Strowes, S. D., ... Carle, G. (2018). Clusters in the expanse: Understanding and unbiasing IPv6 Hitlists. In IMC 2018 - Proceedings of the Internet Measurement Conference (pp. 364-378). Association for Computing Machinery (ACM). https://doi.org/10.1145/3278532.3278564
    Gasser, Oliver ; Lone, Qasim ; Scheitle, Quirin ; Korczyński, Maciej ; Foremski, Pawel ; Strowes, Stephen D. ; Hendriks, Luuk ; Carle, Georg. / Clusters in the expanse : Understanding and unbiasing IPv6 Hitlists. IMC 2018 - Proceedings of the Internet Measurement Conference. Association for Computing Machinery (ACM), 2018. pp. 364-378
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    title = "Clusters in the expanse: Understanding and unbiasing IPv6 Hitlists",
    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 have proposed the use of target lists of IPv6 addresses, called IPv6 hitlists. In this paper, we show that addresses in IPv6 hitlists are heavily clustered. We present novel techniques that allow IPv6 hitlists to be pushed 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 leveraging crowdsourcing. To encourage reproducibility in network measurement research and to serve as a starting point for future IPv6 studies, we publish source code, analysis tools, and data.",
    keywords = "Aliasing, Clustering, Entropy, Hitlist, IPv6",
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    Gasser, O, Lone, Q, Scheitle, Q, Korczyński, M, Foremski, P, Strowes, SD, Hendriks, L & Carle, G 2018, Clusters in the expanse: Understanding and unbiasing IPv6 Hitlists. in IMC 2018 - Proceedings of the Internet Measurement Conference. Association for Computing Machinery (ACM), pp. 364-378, 18th ACM Internet Measurement Conference 2018, Boston, United States, 31/10/18. https://doi.org/10.1145/3278532.3278564

    Clusters in the expanse : Understanding and unbiasing IPv6 Hitlists. / Gasser, Oliver; Lone, Qasim; Scheitle, Quirin; Korczyński, Maciej; Foremski, Pawel; Strowes, Stephen D.; Hendriks, Luuk; Carle, Georg.

    IMC 2018 - Proceedings of the Internet Measurement Conference. Association for Computing Machinery (ACM), 2018. p. 364-378.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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    Gasser O, Lone Q, Scheitle Q, Korczyński M, Foremski P, Strowes SD et al. Clusters in the expanse: Understanding and unbiasing IPv6 Hitlists. In IMC 2018 - Proceedings of the Internet Measurement Conference. Association for Computing Machinery (ACM). 2018. p. 364-378 https://doi.org/10.1145/3278532.3278564