Tor circuit fingerprinting defenses using adaptive padding
This work addresses privacy vulnerabilities in Tor for users seeking online anonymity, though it is incremental as it builds on existing adaptive padding frameworks.
The paper tackled the problem of Tor circuit fingerprinting, where adversaries can identify traffic types from network traces, and developed defenses using adaptive padding to hide onion service circuits effectively without delays.
Online anonymity and privacy has been based on confusing the adversary by creating indistinguishable network elements. Tor is the largest and most widely deployed anonymity system, designed against realistic modern adversaries. Recently, researchers have managed to fingerprint Tor's circuits -- and hence the type of underlying traffic -- simply by capturing and analyzing traffic traces. In this work, we study the circuit fingerprinting problem, isolating it from website fingerprinting, and revisit previous findings in this model, showing that accurate attacks are possible even when the application-layer traffic is identical. We then proceed to incrementally create defenses against circuit fingerprinting, using a generic adaptive padding framework for Tor based on WTF-PAD. We present a simple defense which delays a fraction of the traffic, as well as a more advanced one which can effectively hide onion service circuits with zero delays. We thoroughly evaluate both defenses, both analytically and experimentally, discovering new subtle fingerprints, but also showing the effectiveness of our defenses.