Stopping Silent Sneaks: Defending against Malicious Mixes with Topological Engineering

TL;DR

This paper introduces Bow-Tie, a novel Mixnet design that enhances user anonymity by addressing practical deployment issues like relay sampling, topology placement, and network churn, making Mixnets more secure and scalable.

Contribution

The paper models stratified Mixnets as a three-stage pipeline and proposes Bow-Tie, which improves anonymity through engineered guard layers and client guard-logic, bridging the gap between theory and real-world deployment.

Findings

Bow-Tie significantly improves user anonymity in dynamic settings.

Bow-Tie maintains comparable anonymity in static settings.

Both guard layer and client guard-logic are essential for optimal performance.

Abstract

Mixnets provide strong meta-data privacy and recent academic research and industrial projects have made strides in making them more secure, performance, and scalable. In this paper, we focus our work on stratified Mixnets -- a popular design with real-world adoption -- and identify that there still exist heretofore inadequately explored practical aspects such as: relay sampling and topology placement, network churn, and risks due to real-world usage patterns. We show that, due to the lack of incorporating these aspects, Mixnets of this type are far more susceptible to user deanonymization than expected. In order to reason and resolve these issues, we model Mixnets as a three-stage ``Sample-Placement-Forward'' pipeline, and using the results of our evaluation propose a novel Mixnet design, Bow-Tie. Bow-Tie mitigates user deanonymization through a novel adaption of Tor's guard design with an engineered guard layer and client guard-logic for stratified mixnets. We show that Bow-Tie has significantly higher user anonymity in the dynamic setting, where the Mixnet is used over a period of time, and is no worse in the static setting, where the user only sends a single message. We show the necessity of both the guard layer and client guard-logic in tandem as well as their individual effect when incorporated into other reference designs. Ultimately, Bow-Tie is a significant step towards addressing the gap between the design of Mixnets and practical deployment and wider adoption because it directly addresses real-world user and Mixnet operator concerns.