This repository contains the artifacts for the following paper:
On the Interplay between TLS Certificates and QUIC Performance
M. Nawrocki, P. F. Tehrani, R. Hiesgen, J. Mücke, T. C. Schmidt, and M. Wählisch
In Proceedings of CoNEXT ’22, December 6–9, 2022, Rome, Italy
ACM, New York, NY, USA, 10 pages
https://doi.org/10.1145/3555050.3569123
We include all data and analysis scripts required to reproduce our results. Additionally, we document our scanning tools. Please see the README
files in each sub-directory for all details.
This repository is structured as follows:
code/
: Contains Jupyter notebook code to reproduce our results.data/
: Contains data required by the Jupyter notebooks.misc/
: Contains additional information on how we performed our scans.
Clone this repository, then:
- Make sure you have Jupyter Notebooks and Python installed.
- Double-check the Python requirements and zstd.
- Prepare the analysis by running the initial notebook 01-Prepare-Dataframes.ipynb once.
- Run all the other notebooks in arbitrary order, i.e., from 02-Section-4.1-Classify-Handshakes.ipynb up to 08-Addendum-Rescan-Confirm-CertReuse.ipynb. If RAM is limited, remember to shutdown notebook kernels after you are done with a notebook.
- Find all results in
./code/plots/
, located here or directly in the notebooks.