Rob G. Jansen, PhD

Computer Scientist, Researcher, and Principal Investigator
U.S. Naval Research Laboratory, Washington, DC, USA

Publication Details

  1. Citation

    Rob JansenMatthew Traudt, and Nicholas Hopper:
    Privacy-Preserving Dynamic Learning of Tor Network Traffic. Conference on Computer and Communication Security, 2018.

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    Our work includes improvements that were merged into Shadow v1.13.0


    Experimentation tools facilitate exploration of Tor performance and security research problems and allow researchers to safely and privately conduct Tor experiments without risking harm to real Tor users. However, researchers using these tools configure them to generate network traffic based on simplifying assumptions and outdated measurements and without understanding the efficacy of their configuration choices. In this work, we design a novel technique for dynamically learning Tor network traffic models using hidden Markov modeling and privacy-preserving measurement techniques. We conduct a safe but detailed measurement study of Tor using 17 relays (∼2% of Tor bandwidth) over the course of 6 months, measuring general statistics and models that can be used to generate a sequence of streams and packets. We show how our measurement results and traffic models can be used to generate traffic flows in private Tor networks and how our models are more realistic than standard and alternative network traffic generation methods.


      title = {Privacy-Preserving Dynamic Learning of Tor Network Traffic},
      author = {Jansen, Rob and Traudt, Matthew and Hopper, Nicholas},
      booktitle = {Conference on Computer and Communication Security},
      year = {2018},
      doi = {10.1145/3243734.3243815},