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Anonymity platforms route the traffic over a network of special routers thatare known as mixes and implement various traffic disruption techniques to hidethe communicating users' identities. Batch mixes in particular anonymizecommunicating peers by allowing message exchange to take place only after asufficient number of messages (a batch) accumulate, thus introducing delay. Weintroduce a queueing model for batch mix and study its delay properties. Ouranalysis shows that delay of a batch mix grows quickly as the batch size getsclose to the number of senders connected to the mix. We then propose arandomized batch mixing strategy and show that it achieves much better delayscaling in terms of the batch size. However, randomization is shown to reducethe anonymity preserving capabilities of the mix. We also observe that queueingmodels are particularly useful to study anonymity metrics that are morepractically relevant such as the time-to-deanonymize metric.

Anonymity Mixes as (Partial) Assembly Queues: Modeling and Analysis