Enemy At the Gateways: Censorship-Resilient Proxy Distribution Using Game Theory

Milad Nasr (University of Massachusetts Amherst), Sadegh Farhang (Pennsylvania State University), Amir Houmansadr (University of Massachusetts Amherst), Jens Grossklags (Technical University of Munich)

A core technique used by popular proxy-based circumvention systems like Tor is to
privately and selectively distribute the IP addresses of circumvention proxies among censored clients to keep them unknown to the censors.

In Tor, for instance, such privately shared proxies are known as bridges.
A key challenge to this mechanism is the insider attack problem:
censoring agents can impersonate benign censored clients in order to learn (and then block) the privately shared circumvention proxies.
To minimize the risks of the insider attack threat,
in-the-wild circumvention systems like Tor use various
proxy assignment mechanisms in order to
minimize the risk of proxy enumeration by the censors, while providing access to a large fraction of censored clients.

Unfortunately, existing proxy assignment mechanisms (like the one used by Tor) are based on ad hoc heuristics that offer no theoretical guarantees and are easily evaded in practice.
In this paper, we take a systematic approach to the problem of proxy distribution in circumvention systems by establishing a game-theoretic framework.
We model the proxy assignment problem as a game between circumvention system operators and the censors, and use game theory to derive the optimal strategies of each of the parties.
Using our framework, we derive the best (optimal) proxy assignment mechanism of a circumvention system like Tor in the presence of the strongest censorship adversary who takes her best censorship actions.

We perform extensive simulations to evaluate our optimal proxy assignment algorithm under various adversarial and network settings. We show that the algorithm has superior performance compared to the state of the art, i.e., provides stronger resistance to censorship even against the strongest censorship adversary.
Our study establishes a generic framework for optimal proxy assignment that can be applied to various types of circumvention systems and under various threat models.
We conclude with lessons and recommendations for the design of proxy-based circumvention systems.