Blending Different Latency Traffic With Beta Mixing

Abstract

We analyze the anonymity provided by continuous mixnets (e.g., Loopix) when messages with different latency requirements are sent through the same network. The anonymity provided by existing mixnets that offer bounded latency guarantees has only been studied considering that all the traffic in the network follows the same latency distribution. In this work we evaluate whether it is beneficial to aggregate different types of traffic in the same network or to keep them separate, when the latency distributions are exponential and the traffic arrivals are a poisson process --- as is the case in Loopix and related designs. We present a novel evaluation method to analyze the leakage to the adversary when multiple different types of traffic are sent through the same network of continuous mixes. We apply the method to empirically evaluate the end-to-end anonymity (in terms of entropy) for each type of traffic in the presence of a global passive adversary that may additionally compromise a constant fraction of mixes or may have knowledge about the type of traffic of network output messages. Finally we show via empirical evaluation using our analytical framework that it is beneficial for anonymity to blend different types of traffic in the same mixnet.