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<!doctype html>
<html lang="en">
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
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font-size: 2rem;
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<title>IPv6 Hitlist</title>
</head>
<body>
<!-- Put nav into container to center it on the page -->
<nav class="navbar navbar-expand-lg navbar-light bg-light fixed-top">
<div class="container">
<a class="navbar-brand" href="#">↑</a>
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<span class="navbar-toggler-icon"></span>
</button>
<div class="collapse navbar-collapse" id="navbarNavAltMarkup">
<div class="navbar-nav container">
<a class="nav-item nav-link" href="#hitlist">IPv6 Hitlist Service</a>
<a class="nav-item nav-link" href="#tools">Software and Tools</a>
<a class="nav-item nav-link" href="#paper2023">Paper (TMA 2023)</a>
<a class="nav-item nav-link" href="#paper2022">Paper (IMC 2022)</a>
<a class="nav-item nav-link" href="#paper2018">Paper (IMC 2018)</a>
<a class="nav-item nav-link" href="#reproduc">Reproducibility</a>
<a class="nav-item nav-link" href="#contact">Contact</a>
<a class="nav-item nav-link" href="#partners">Partners</a>
<a class="nav-item nav-link" href="#data-providers">Data Providers</a>
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<a class="github-fork-ribbon right-bottom fixed" href="https://github.com/ipv6hitlist/ipv6hitlist.github.io" data-ribbon="Fork me on GitHub" title="Fork me on GitHub">Fork me on GitHub</a>
<div class="container">
<h2 class="topmargin">Understanding and Unbiasing IPv6 Hitlists</h2>
On this website we present additional information about our IMC papers <i>"Clusters in the Expanse: Understanding and Unbiasing IPv6 Hitlists"</i> and <i>"Rusty Clusters? Dusting an IPv6 Research Foundation"</i>, and provide access to our IPv6 Hitlist Service.
<h2 id="hitlist">IPv6 Hitlist Service</h2>
We provide an IPv6 Hitlist Service where we publish <b>responsive IPv6 addresses, address categories, aliased prefixes, and non-aliased prefixes</b> to interested researchers.
The IPv6 Hitlist Service consists of an openly accessible one and a registration-first service.
<h3>Hitlist addresses</h3>
This graph shows the development of the <b>full, aliased and non-aliased</b> hitlist over time.
<br>
<div id="plot-input" style="min-width: 310px; height: 400px; margin: 0 auto"></div>
<br>
<h3>Responsive addresses</h3>
Here, the development of the <b>different protocol responses</b> over time is shown. We scan five different protocols, an additional graph shows the amount of IP addresses which respond to at least one of the protocols.
<div id="plot-responsive" style="min-width: 310px; height: 400px; margin: 0 auto"></div>
The plot of responsive addresses is an updated version.
We removed all responses to the UDP/53 scan injected by the Great Firewall of China.
The original plot and additional information is provided here:
<ul>
<li><a href="gfw-filter/">Great Firewall of China Hitlist Filter</a></li>
</ul>
We provide both filtered and unfiltered, historic UPD/53 files for registered users.
<br>
<h3>Categorized addresses</h3>
Lastly, the <b>network categories</b> represented in the Hitlist can be seen.
Via the dropdown the categories represented in the hitlist, the total responsive addresses, or the responsive addresses per protocol may be chosen.
The categories are filtered with <a href="https://www.peeringdb.com/">PeeringDB</a>. For the details, see the <a href="#paper2023">2023 Paper</a>.
<div style="text-align: center; padding-top: 30px;">
Select the data type:
<select id="categ_content_select">
<option selected="selected">Responsive Adresses</option>
<option>Hitlist Adresses</option>
<option>TCP/80 Responsive</option>
<option>TCP/443 Responsive</option>
<option>UDP/53 Responsive</option>
<option>UDP/443 Responsive</option>
<option>ICMP Responsive</option>
</select>
</div>
<div id="plot-categories" style="min-width: 310px; height: 400px; margin: 0 auto; padding-top: 20px"></div>
<h4>Openly Accessible Service</h4>
You can use the weekly generated list of responsive IPv6 addresses, aliased prefixes, and non-aliased prefixes without registration:
<ul>
<li><a href="https://alcatraz.net.in.tum.de/ipv6-hitlist-service/open/responsive-addresses.txt.xz">Responsive IPv6 addresses</a></li>
<li><a href="https://alcatraz.net.in.tum.de/ipv6-hitlist-service/open/aliased-prefixes.txt.xz">Aliased prefixes</a></li>
<li><a href="https://alcatraz.net.in.tum.de/ipv6-hitlist-service/open/non-aliased-prefixes.txt.xz">Non-aliased prefixes</a></li>
</ul>
The responsive addresses include addresses from non-aliased prefixes only.
Please see the <a href="#apd-lpm">notes about aliased prefixes</a> below to make use of them.
<h4>Registration-First Service</h4>
We provide additional data which can be used to conduct in-depth research on IPv6 networks and addresses.
This includes:
<ul>
<li>Daily input addresses for scanning, including aliased and non-responsive addresses</li>
<li>Daily responsive IPv6 addresses, aliased prefixes, and non-aliased prefixes</li>
<li>Raw ZMap output files including TCP options (e.g. usable for further alias analysis)</li>
<li>Access to complete historical data</li>
</ul>
To get <b>free access</b> to this registration-first service, you can send a quick
<a href="mailto:[email protected]?subject=Access%20to%20IPv6%20Hitlist%20Service&body=Hi,%0A%0A%20please%20grant%20me%20access%20to%20the%20IPv6%20Hitlist%20Service.%20My%20name%20is%20YOURNAMEHERE,%20my%20affiliation%20is%20CHANGEME%20and%20I%20want%20to%20use%20the%20data%20for%20FILLTHIS.%20%0A%0AThank%20you,%20kind%20regards">registration email</a>.
We use the gathered data for statistical purposes and might very occasionally send a survey or other requests for feedback.
<h4>Referencing the Hitlist Service</h4>
If you are using data from the IPv6 Hitlist Service in your publication, please refer to it with the following references:
<br>
<small>
<code>
@inproceedings{gasser2018clusters,<br>
title = {Clusters in the Expanse: Understanding and Unbiasing IPv6 Hitlists},<br>
author = {Gasser, Oliver and Scheitle, Quirin and Foremski, Pawel and Lone, Qasim and Korczynski, Maciej and Strowes, Stephen D. and Hendriks, Luuk and Carle, Georg},<br>
booktitle = {Proceedings of the 2018 Internet Measurement Conference},<br>
year = {2018},<br>
location = {Boston, MA, USA},<br>
numpages = {15},<br>
doi = {10.1145/3278532.3278564},<br>
publisher = {ACM},<br>
address = {New York, NY, USA},<br>
}
</code>
</small>
<small>
<code>
@inproceedings{zirngibl2022rustyclusters,<br>
title = {Rusty Clusters? Dusting an IPv6 Research Foundation},<br>
author = {Zirngibl, Johannes and Steger, Lion and Sattler, Patrick and Gasser, Oliver and Carle, Georg},<br>
booktitle = {Proceedings of the 2022 Internet Measurement Conference},<br>
year = {2022},<br>
location = {Nice, France},<br>
numpages = {15},<br>
doi = {10.1145/3517745.3561440},<br>
publisher = {ACM},<br>
address = {New York, NY, USA},<br>
}
</code>
</small>
<small>
<code>
@inproceedings{steger2023targetacquired,<br>
title = {Target Acquired? Evaluating Target Generation Algorithms for IPv6},<br>
author = {Steger, Lion and Kuang, Liming and Zirngibl, Johannes and Carle, Georg and Gasser, Oliver},<br>
booktitle = {Proceedings of the Network Traffic Measurement and Analysis Conference (TMA)},<br>
year = {2023},<br>
month = jun,<br>
location = {Naples, Italy},<br>
publisher = {},<br>
}
</code>
</small>
<p>
The same reference applies to the open and registered service. <b><a href="gasser2018clusters.bib">[bib]</a>, <a href="zirngibl2022rustyclusters.bib">[bib]</a> and <a href="steger2023targetacquired.bib">[bib]</a></b>
<h2 id="tools">Software and Tools</h2>
During our IPv6 hitlist analysis we developed software to analyze and understand IPv6 hitlist.
We publish the following software and tools for use by the scientific community:
<ul>
<li><a href="#zmapv6">ZMapv6</a></li>
<li><a href="#zesplot">zesplot</a></li>
<li><a href="#entropy-clustering">Entropy Clustering</a></li>
<li><a href="#entropy-ip">Entropy/IP</a></li>
<li><a href="#entropy-ip-reimp">New Entropy/IP Generator</a></li>
<li><a href="#apd-lpm">Longest prefix matching for aliased prefixes</a></li>
<li><a href="#distance-clustering">Distance Clustering</a></li>
<li><a href="#gfw-filter"> GFW filter</a></li>
</ul>
<h4 id="zmapv6">ZMapv6</h4>
We extend the original ZMap to add IPv6 capabilities.
ZMapv6 supports the following new IPv6-specific probe modules:
<ul>
<li>ICMPv6 Echo Request</li>
<li>IPv6 TCP SYN (any port)</li>
<li>IPV6 UDP (any port and payload)</li>
</ul>
ZMapv6 can read IPv6 target addresses from a file or from standard input.
<br>
Source: <a href="https://github.com/tumi8/zmap">github.com/tumi8/zmap</a>
<h4 id="zesplot">zesplot</h4>
zesplot is a tool to visualize IPv6 networks. It uses the concept of
squarified treemaps and plots IPv6 networks in a space-filling way. Note
that unlike a Hilbert curve visualizing IPv4 address space, zesplot does
not plot the entire IPv6 address space.
<br>
Source: <a href="https://github.com/zesplot/zesplot">github.com/zesplot/zesplot</a>
<h4 id="entropy-clustering">Entropy Clustering</h4>
Entropy Clustering is a software to find and visualize clusters in IPv6 addressing schemes.
<br>
Source: <a href="https://github.com/pforemski/entropy-clustering">github.com/pforemski/entropy-clustering</a>
<h4 id="entropy-ip">Entropy/IP</h4>
Entropy/IP is a software to find patterns in IPv6 addresses and generate addresses based on these patterns.
Entropy/IP was presented during the 2016 Internet Measurement Conference.
For more information see the <a href="http://www.entropy-ip.com/">Entropy/IP website</a>.
The Entropy/IP software is published by Akamai.
<br>
Source: <a href="https://github.com/akamai/entropy-ip">github.com/akamai/entropy-ip</a>
<h4 id="entropy-ip-reimp">New Entropy/IP Generator</h4>
This generator uses the output of Entropy/IP to generate IPv6 addresses which follow the specified model.
<br>
Source: <a href="https://github.com/pforemski/eip-generator">github.com/pforemski/eip-generator</a>
<h4 id="apd-lpm">Longest prefix matching for aliased prefixes</h4>
To make use of our published lists of aliased and non-aliased prefixes for your custom IPv6 address list, you need to perform longest prefix matching.
This ensures that your addresses are matched to the longest aliased or non-aliased prefix.
For your convenience we publish a simple Python script and a Go tool for this purpose.
<br>
Python source: <a href="lpm/aliases-lpm.py">aliases-lpm.py</a>
<br>
Go source: <a href="lpm/aliases-lpm.go">aliases-lpm.go</a>
<h4 id="distance-clustering">Distance Clustering</h4>
This method generates IPv6 address candidates from a seed list.
It extends more densely clustered address regions that show high entropy in the last nibble(s) of the address.
Note, these regions are not fully responsive but only densely populated.
<br>
Python source: <a href="distance-clustering/"> distance-clustering</a>
<h4 id="gfw-filter">GFW filer</h4>
We provide a script to filter the output of UDP/53 scans from the impact of the GFW.
<br>
Python source: <a href="gfw-filter/filter_gfw.py">filter_gfw.py</a>
<h2 id="paper2023">Target Acquired? Evaluating Target Generation Algorithms for IPv6</h2>
<b> Abstract.</b> Internet measurements are a crucial foundation of
IPv6-related research. Due to the infeasibility of full address space
scans for IPv6 however, those measurements rely on collections
of reliably responsive, unbiased addresses, as provided e.g., by
the IPv6 Hitlist service. Although used for various use cases, the
hitlist provides an unfiltered list of responsive addresses, the hosts
behind which can come from a range of different networks and
devices, such as web servers, customer-premises equipment (CPE)
devices, and Internet infrastructure. <br>
In this paper, we demonstrate the importance of tailoring
hitlists in accordance with the research goal in question. By
using PeeringDB we classify hitlist addresses into six different
network categories, uncovering that 42% of hitlist addresses are
in ISP networks. Moreover, we show the different behavior of
those addresses depending on their respective category, e.g., ISP
addresses exhibiting a relatively low lifetime. Furthermore, we
analyze different Target Generation Algorithms (TGAs), which are
used to increase the coverage of IPv6 measurements by generating
new responsive targets for scans. We evaluate their performance
under various conditions and find generated addresses to show
vastly differing responsiveness levels for different TGAs.
<br>
<b>Paper. </b> Read the final version of our paper here: <b><a href="http://www.net.in.tum.de/fileadmin/bibtex/publications/papers/steger2023targetacquired.pdf">[PDF]</a></b>
<br>
<b>Authors.</b>
<a href="https://www.net.in.tum.de/members/stegerl/">Lion Steger</a>,
Liming Kuang,
<a href="https://www.net.in.tum.de/members/zirngibl/">Johannes Zirngibl</a>,
<a href="https://www.net.in.tum.de/members/carle/">Georg Carle</a>,
<a href="https://olivergasser.net/">Oliver Gasser</a>.
<h2 id="paper2022">Rusty Clusters? Dusting an IPv6 Research Foundation</h2>
<b> Abstract.</b> The long-running IPv6 Hitlist service is an important
foundation for IPv6 measurement studies. It helps to overcome infeasible,
complete address space scans by collecting valuable, unbiased IPv6 address
candidates and their responsiveness. However, the Internet itself is a
quickly changing ecosystem that can effect long-running services, potentially
inducing new biases and obscurities into ongoing data collection means.
Frequent analyses but also updates are necessary to enable a valuable service
to the community.<br>
In this paper, we show that the existing hitlist is highly impacted by the
Great Firewall of China and we offer a cleaned view on its development. While
the accumulated input shows an increasing bias towards some networks, the
cleaned set of responsive addresses is well distributed and shows a steady
increase.<br>
Although it is a best practice to remove aliased prefixes from IPv6 hitlists,
we show that this removes not only single hosts responsive to complete
prefixes, but also major content delivery networks. More than 98% of all
IPv6 addresses announced by Fastly are labeled as aliased and Cloudflare
prefixes hosting more than 10M domains are excluded. Depending on the
hitlist usage, e.g., higher layer protocol scans, inclusion of addresses
from these providers can be valuable.<br>
Lastly, we evaluate different new address candidate sources, including
target generation algorithms. We show that a combination of different
methodologies is able to identify 5.6M new, responsive addresses. This
accounts for an increase by 174% and combined with the current IPv6 Hitlist,
we identify 8.8M responsive addresses.
<br>
<b>Paper. </b> Read the final version of our paper here: <b><a href="http://www.net.in.tum.de/fileadmin/bibtex/publications/papers/zirngibl2022rustyclusters.pdf">[PDF]</a></b>
<br>
<b>Authors.</b>
<a href="https://www.net.in.tum.de/members/zirngibl/">Johannes Zirngibl</a>,
<a href="https://www.net.in.tum.de/members/stegerl/">Lion Steger</a>,
<a href="https://www.net.in.tum.de/members/sattler/">Patrick Sattler</a>,
<a href="https://olivergasser.net/">Oliver Gasser</a>,
<a href="https://www.net.in.tum.de/members/carle/">Georg Carle</a>.
<h2 id="paper2018">Clusters in the Expanse: Understanding and Unbiasing IPv6 Hitlists</h2>
<b>Abstract.</b> 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.<br>
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.<br>
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.
<br>
<b>Paper.</b> Read the final version of our paper at arXiv.org:
<b><a href="https://arxiv.org/abs/1806.01633">[abstract]</a></b> and
<b><a href="https://arxiv.org/pdf/1806.01633.pdf">[PDF]</a></b>.
<br>
<b>Authors.</b> <a href="https://olivergasser.net/">Oliver Gasser</a>, <a href="https://www.net.in.tum.de/members/scheitle/">Quirin Scheitle</a>, <a href="http://www.foremski.pl/">Paweł Foremski</a>, <a href="https://drakkar.imag.fr/spip.php?auteur91">Qasim Lone</a>,
<a href="http://mkorczynski.com/">Maciej Korczyński</a>, <a href="https://sdstrowes.co.uk/">Stephen D. Strowes</a>, <a href="https://blog.luukhendriks.eu/">Luuk Hendriks</a>, <a href="https://www.net.in.tum.de/members/carle/">Georg Carle</a>.
<h4>Additional Plots</h4>
We provide additional plots for in-depth analysis accompanying the evaluations in our paper.<br>
<p>
<b>Interactive zesplot plots</b>
<ul>
<li><a href="zesplot/">Interactive zesplots of input sets, responses, aliased prefix detection and entropy clustering</a></li>
</ul>
<p>
<b>Entropy clustering plots</b>
<ul>
<li><a href="eip/">Entropy clustering of hitlist IPv6 addresses</a></li>
<li><a href="eip-scanning/">Entropy clustering of responsive IPv6 addresses</a></li>
</ul>
<p>
<b>Responsiveness over time</b>
<ul>
<li><a href="probing/">Responsiveness over time for each protocol and source</a></li>
</ul>
<h2 id="reproduc">Reproducibility</h2>
<h4>Target Acquired? Evaluating Target Generation Algorithms for IPv6</h4>
We publish data and scripts to reproduce our analysis at the <a href="https://mediatum.ub.tum.de/1709953"> TUM university library</a> to guarantee long-term availability.
<br>
Dataset DOI: <a href="https://doi.org/10.14459/2023mp1709953">10.14459/2023mp1709953</a>
<p style="color: red; margin-top: 15px">NOTE: The dataset is missing some scripts needed for the reproducibility</p> Please find the scripts, without the data, in our <a href="https://github.com/tumi8/tma-23-target-generation"> GitHub repository</a>
<h4>Rusty Clusters? Dusting an IPv6 Research Foundation</h4>
We publish data and scripts to reproduce our analysis at the <a href="https://mediatum.ub.tum.de/1686542"> TUM university library</a> to guarantee long-term availability.
<br>
Dataset DOI: <a href="https://doi.org/10.14459/2022mp1686542">10.14459/2022mp1686542 </a>
<h4>Clusters in the Expanse: Understanding and Unbiasing IPv6 Hitlists</h4>
We publish data and scripts to reproduce our analysis at the
<a href="https://mediatum.ub.tum.de/1452739">TUM university library</a> to guarantee long-term availability.
<br>
Dataset DOI: <a href="https://dx.doi.org/10.14459/2018mp1452739">10.14459/2018mp1452739</a>
<br>
<p>
<b>Reproducibility update 2019-04-10</b>
We update the requirements.txt file and provide additional information in the README.md file.
You can download the updated files from <a href="reproducibility-updates/2019-04-10/">this directory</a>.
<br>
<p>
<b>SIGCOMM Artifacts Evaluation Badges</b>
We were awarded all three badges by the <a href="https://www.sigcomm.org/content/sigcomm-artifacts-evaluation-committee">SIGCOMM Artifacts Evaluation Committee</a> underlining that our published data and scripts are available, functional, and reusable.
<div class="row align-items-center">
<div class="col-md-3">
<img src="sigcommae/artifacts_available.jpg" alt="SIGCOMM Artifacts Evaluation available badge" class="img-fluid"/>
</div>
<div class="col-md-3">
<img src="sigcommae/artifacts_evaluated_functional.jpg" alt="SIGCOMM Artifacts Evaluation functional badge" class="img-fluid"/>
</div>
<div class="col-md-3">
<img src="sigcommae/artifacts_evaluated_reusable.jpg" alt="SIGCOMM Artifacts Evaluation reusable badge" class="img-fluid"/>
</div>
</div>
<h2 id="contact">Contact</h2>
<b><a href="https://olivergasser.net/">Oliver Gasser</a></b>: <b>oliver.gasser</b> [AT] <b>mpi-inf.mpg.de</b><br>
<b><a href="https://www.net.in.tum.de/members/zirngibl/">Johannes Zirngibl</a></b>: <b>zirngibl</b> [AT] <b>net.in.tum.de</b><br>
<b><a href="https://www.net.in.tum.de/members/stegerl/">Lion Steger</a></b>: <b>stegerl</b> [AT] <b>net.in.tum.de</b>
<h2 id="partners">Partners</h2>
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<a href="https://www.tum.de/nc/en/homepage/"><img src="logos/TUM_Logo_extern_mt_EN_RGB_p.png" alt="TUM logo" class="img-fluid"/></a>
</div>
<div class="col-md-3">
<a href="https://www.iitis.pl/en"><img src="logos/itis.png" alt="IITiS logo" class="img-fluid"/></a>
</div>
<div class="col-md-3">
<a href="https://www.tudelft.nl/en/"><img src="logos/tudelft.jpg" alt="TU Delft logo" class="img-fluid"/></a>
</div>
</div>
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<a href="https://www.univ-grenoble-alpes.fr/en/"><img src="logos/logo-uga.png" alt="University Grenoble Alpes logo" class="img-fluid"/></a>
</div>
<div class="col-md-3">
<a href="https://www.ripe.net/"><img src="logos/RIPE_NCC_Logo2015.png" alt="RIPE NCC logo" class="img-fluid"/></a>
</div>
<div class="col-md-3">
<a href="https://www.utwente.nl/en/"><img src="logos/UTEN.png" alt="UTwente logo" class="img-fluid"/></a>
</div>
</div>
<div class="row align-items-center">
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<a href="https://www.mpi-inf.mpg.de/home"><img src="logos/logo_mpi.png" alt="MPI logo" class="img-fluid"/></a>
</div>
</div>
<h2 id="data-providers">External Data Providers</h2>
<div class="row align-items-center">
<div class="col-md-3">
<a href="https://ipinfo.io"><img src="logos/ipinfo.svg" alt="IPinfo logo" class="img-fluid"/></a>
</div>
<div class="col-md-3">
<a href="https://opendata.rapid7.com/"><img src="logos/rapid7.png" alt="Rapid7 logo" class="img-fluid"/></a>
</div>
<div class="col-md-3">
<a href="https://atlas.ripe.net/"><img src="logos/ripeatlas.png" alt="RIPE Atlas logo" class="img-fluid"/></a>
</div>
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