WFDefProxy: Modularly Implementing and Empirically Evaluating Website Fingerprinting Defenses
Tor, an onion-routing anonymity network, has been shown to be vulnerable to Website Fingerprinting (WF), which de-anonymizes web browsing by analyzing the unique characteristics of the encrypted network traffic. Although many defenses have been proposed, few have been implemented and tested in the r...
Saved in:
Main Authors | , , , |
---|---|
Format | Journal Article |
Language | English |
Published |
24.11.2021
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | Tor, an onion-routing anonymity network, has been shown to be vulnerable to
Website Fingerprinting (WF), which de-anonymizes web browsing by analyzing the
unique characteristics of the encrypted network traffic. Although many defenses
have been proposed, few have been implemented and tested in the real world;
others were only simulated. Due to its synthetic nature, simulation may fail to
capture the real performance of these defenses. To figure out how these
defenses perform in the real world, we propose WFDefProxy, a general platform
for WF defense implementation on Tor using pluggable transports. We create the
first full implementation of three WF defenses: FRONT, Tamaraw and Random-WT.
We evaluate each defense in both simulation and implementation to compare their
results, and we find that simulation correctly captures the strength of each
defense against attacks. In addition, we confirm that Random-WT is not
effective in both simulation and implementation, reducing the strongest
attacker's accuracy by only 7%.
We also found a minor difference in overhead between simulation and
implementation. We analyze how this may be due to assumptions made in
simulation regarding packet delays and queuing, or the soft stop condition we
implemented in WFDefProxy to detect the end of a page load. The implementation
of FRONT cost about 23% more data overhead than simulation, while the
implementation of Tamaraw cost about 28% - 45% less data overhead. In addition,
the implementation of Tamaraw incurred only 21% time overhead, compared to 51%
- 242% estimated by simulation in previous work. |
---|---|
DOI: | 10.48550/arxiv.2111.12629 |