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Drawn Apart

Artifacts for "DRAWN APART : A Device Identification Technique based on Remote GPU Fingerprinting", by Tomer Laor, Naif Mehanna, Vitaly Dyadyuk, Antonin Durey, Pierre Laperdrix, Clémentine Maurice, Yossi Oren, Romain Rouvoy, Walter Rudametkin, and Yuval Yarom

Demo pages

You will find below three distinct demo pages, each testing a different timing measurement method.

Note that both the GPU and Offscreen methods are only available by default at the moment on Chromium-based browsers (see progress on the support of OffscreenCanvas for Firefox and Safari).

Python notebook

Our classification over real data can be viewed using the interactive Python notebook at the following link: https://colab.research.google.com/github/DrawnApart/DrawnApart/blob/master/drawnapart_demo.ipynb

The raw data is contained in the different tgz files present at the root of this repository.

The revisited FPStalker code with DrawnApart is also available at the root of this repository, under the name "fpstalker_drawnapart.ipynb". For privacy-related reasons, we use a bogus dataset for the execution. It can be executed by visiting the interactive notebook at the following link:
https://colab.research.google.com/github/DrawnApart/DrawnApart/blob/master/fpstalker_drawnapart.ipynb

Videos

To assess the robustness of our Drawn Apart method, we filmed two experiments where we swapped hardware between two computers.

For More Information

Please see the paper's official webpage

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  • Jupyter Notebook 67.2%
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  • HTML 14.3%
  • CSS 0.4%