First, we present a new Tor network modeling methodology that produces more representative Tor networks as well as new and improved experimentation tools that run Tor simulations faster and at a larger scale than was previously possible. In this paper, we build foundations upon which we improve the Tor experimental method. Therefore, we call into question the practical meaning of any conclusions that are drawn without considering the statistical significance of the reported results.

But because the simulations are run in sampled Tor networks, it is possible that sampling error alone could cause the observed effects.

The standard practice for previous research attempting to enhance Tor performance is to draw conclusions from the observed results of a single simulation for standard Tor and for each research variant. Tor is a popular low-latency anonymous communication system that focuses on usability and performance: a faster network will attract more users, which in turn will improve the anonymity of everyone using the system.

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