tornettools

tornettools is a utility to guide you through the Tor network experimentation process using Shadow, by assisting with the following experimentation steps:

stage: Process Tor metrics data for staging network generation
generate: Generate TorNet network configurations
simulate: Run a TorNet simulation in Shadow
parse: Parse useful data from simulation log files
plot: Plot previously parsed data to visualize results
archive: Cleanup and compress Shadow simulation data

The configuration files that are generated can be run in the Shadow network simulator; NetMirage and Chutney may eventually support the files generated with this tool.

The generated networks include the use of TGen for the generation of realistic background traffic, and OnionTrace for the collection of information from Tor throughout an experiment.

Citation

This tool was initially created as part of the following research publication. Please cite this paper if you use this tool in your work:

Once is Never Enough: Foundations for Sound Statistical Inference in Tor Network Experimentation
Proceedings of the 30th USENIX Security Symposium (Sec 2021)
by Rob Jansen, Justin Tracey, and Ian Goldberg

Here is a bibtex entry for latex users:

@inproceedings{neverenough-sec2021,
  author = {Rob Jansen and Justin Tracey and Ian Goldberg},
  title = {Once is Never Enough: Foundations for Sound Statistical Inference in {Tor} Network Experimentation},
  booktitle = {30th USENIX Security Symposium (Sec)},
  year = {2021},
  note = {See also \url{https://neverenough-sec2021.github.io}},
}

Note about versioning

Development of tornettools is slow and typically focuses on changes that keep the tool in sync with changes being made in Shadow. Thus, you should generally just ignore the tornettools version numbers and use the latest version. Sometimes you might want to pin to a specific version that is known to be compatible with your version of Shadow, e.g., when building container images, and in this case we recommend pinning to a specific commit hash.

We do use version numbers, but they have historically been based on vibes rather than semver and we don't want to introduce the overhead of following a more strict policy than that.

setup is easy with virtualenv and pip

python3 -m venv toolsenv
source toolsenv/bin/activate
pip install -r requirements.txt
# if you plan to make changes to tornettools, you can add the '--editable' pip install flag
# to avoid the need to re-run 'pip install' after every modification:
# https://pip.pypa.io/en/stable/topics/local-project-installs/#editable-installs
pip install --ignore-installed .

read the help menus

tornettools -h
tornettools stage -h
tornettools generate -h
tornettools simulate -h
tornettools parse -h
tornettools plot -h
tornettools archive -h

grab the data we need

wget https://collector.torproject.org/archive/relay-descriptors/consensuses/consensuses-2023-04.tar.xz
wget https://collector.torproject.org/archive/relay-descriptors/server-descriptors/server-descriptors-2023-04.tar.xz
wget https://metrics.torproject.org/userstats-relay-country.csv
wget https://collector.torproject.org/archive/onionperf/onionperf-2023-04.tar.xz
wget -O bandwidth-2023-04.csv "https://metrics.torproject.org/bandwidth.csv?start=2023-04-01&end=2023-04-30"

extract

tar xaf consensuses-2023-04.tar.xz
tar xaf server-descriptors-2023-04.tar.xz
tar xaf onionperf-2023-04.tar.xz

we also utilize privcount Tor traffic model measurements

git clone https://github.com/tmodel-ccs2018/tmodel-ccs2018.github.io.git

we also need tor

sudo apt-get install openssl libssl-dev libevent-dev build-essential automake zlib1g zlib1g-dev
git clone https://git.torproject.org/tor.git
cd tor
./autogen.sh
./configure --disable-asciidoc --disable-unittests --disable-manpage --disable-html-manual
make -j$(nproc)
cd ..

install additional executables used by tornettools

tornettools also uses the faketime, dstat, free, and xz command-line tools. On Ubuntu these can be installed with:

sudo apt-get install faketime dstat procps xz-utils

in order to generate, we need a tor and tor-gencert binaries (to generate relay keys)

export PATH=${PATH}:`pwd`/tor/src/core/or:`pwd`/tor/src/app:`pwd`/tor/src/tools

stage first, process relay and user info

tornettools stage \
    consensuses-2023-04 \
    server-descriptors-2023-04 \
    userstats-relay-country.csv \
    tmodel-ccs2018.github.io \
    --onionperf_data_path onionperf-2023-04 \
    --bandwidth_data_path bandwidth-2023-04.csv \
    --geoip_path tor/src/config/geoip

now we can used the staged files to generate many times

For example, use --network_scale 0.01 to generate a private Tor network at '1%' the scale of public Tor:

tornettools generate \
    relayinfo_staging_2023-04-01--2023-04-30.json \
    userinfo_staging_2023-04-01--2023-04-30.json \
    networkinfo_staging.gml \
    tmodel-ccs2018.github.io \
    --network_scale 0.01 \
    --prefix tornet-0.01

now you can run a simulation and process the results

Make sure you have already installed shadow, tgen, and oniontrace.

Note that simulating a '1%' Tor network for 60 simulation minutes can take as much as 30GiB of RAM.

tornettools simulate tornet-0.01
tornettools parse tornet-0.01
tornettools plot \
    tornet-0.01 \
    --tor_metrics_path tor_metrics_2023-04-01--2023-04-30.json \
    --prefix pdfs
tornettools archive tornet-0.01

Performance metrics are plotted in the graph files in the pdfs directory.

jdejaegh / tornettools Goto Github PK

tornettools's Introduction