RECENT PUBLICATIONS

1. Paul Syverson, Rasmus Dahlberg, Tobias Pulls, and Rob Jansen:

   Onion-Location Measurements and Fingerprinting. Proceedings on Privacy Enhancing Technologies, vol. 2025, no. 2, 2025.

   pdf abs bib details

   Onion-Location makes it easy for websites offering onion service access to support automatic discovery in Tor Browser of the random-looking onion address associated with their domain. We provide the first measurement study of how many websites are currently using Onion-Location. We also describe the open-source tools we created to conduct the study. Onion-Location has been criticized elsewhere for its lack of transparency and vulnerability to blocking. Perhaps even more troubling, we show that Onion-Location is vulnerable to very accurate fingerprinting. We present recommended changes to and alternatives to Onion-Location as well as steps towards even more secure onion discovery and association.

   @article{onionloc-popets2025,
     title = {Onion-Location Measurements and Fingerprinting},
     author = {Syverson, Paul and Dahlberg, Rasmus and Pulls, Tobias and Jansen, Rob},
     journal = {Proceedings on Privacy Enhancing Technologies},
     volume = {2025},
     number = {2},
     year = {2025},
     doi = {10.56553/popets-2025-0074},
   }

2. Rob Jansen, Ryan Wails, and Aaron Johnson:

   Repositioning Real-World Website Fingerprinting on Tor. Workshop on Privacy in the Electronic Society, 2024.

   pdf abs bib details

   Website fingerprinting (WF) is a potentially devastating attack against Tor because it can break anonymity by linking a Tor user to their purportedly unlinkable internet destinations. Previous work proposes that an adversary trains WF classifiers either on synthetic traces that are programmatically generated using automated tools, or on real-world traces collected from one or more Tor exit relays. However, no existing work accurately represents a real-world threat model in which a WF adversary’s classifiers must be tested against real-world entry traces that are naturally created by real Tor users. In this paper we present Retracer, a novel method for producing labeled entry traces of genuine Tor traffic patterns. Retracer uses high-fidelity network simulation to accurately transform real-world exit traces into entry traces prior to training and testing WF classifiers. After first demonstrating that Retracer accurately transforms exit traces into entry traces, we then apply it to the recently released GTT23 dataset in a WF evaluation in which more than 3500 classifiers are tested against, for the first time, labeled entry traces of real Tor traffic patterns. Our evaluation yields the best available estimate of the performance an adversary can achieve when directing WF attacks at real Tor users.

   @inproceedings{retracer-wpes2024,
     title = {Repositioning Real-World Website Fingerprinting on Tor},
     author = {Jansen, Rob and Wails, Ryan and Johnson, Aaron},
     booktitle = {Workshop on Privacy in the Electronic Society},
     year = {2024},
     doi = {10.1145/3689943.3695047},
   }

3. Anna Harbluk Lorimer,  Rob Jansen, and Nick Feamster:

   Extended abstract: Traffic Splitting for Pluggable Transports. Workshop on Free and Open Communication on the Internet, 2024.

   pdf abs bib details

   As censors continue to develop more advanced technologies to police access to the Internet, new techniques are also needed to promote Internet freedom. Traffic splitting is one technique that has been shown to defend against various privacy attacks and to improve network performance, but it has not been evaluated in the context of censorship-resistant systems. In this extended abstract we outline a design for traffic splitting for pluggable transports that uses what we call a "shim" pluggable transport and modified Tor Bridges as proxies. We describe our hypotheses and how we plan to evaluate our implementation to determine the extent to which pluggable transports that employ traffic splitting can improve performance, protect against website fingerprinting attacks, and improve resistance to detection and blocking by a censor.

   @misc{ptsplit-foci2024,
     title = {Traffic Splitting for Pluggable Transports},
     author = {Lorimer, Anna Harbluk and Jansen, Rob and Feamster, Nick},
     howpublished = {Workshop on Free and Open Communication on the Internet},
     year = {2024},
     note = {Extended abstract},
   }