The provision of content confidentiality via message encryption is by no means sufficient when facing the significant privacy risks present in online communications. Indeed, the privacy literature abounds with examples of traffic analysis techniques aimed to reveal a great deal of information, merely from the knowledge, even if probabilistic, of who is communicating with whom, when, and how frequently. Anonymous-communication systems emerge as a response against such traffic analysis threats.

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... xes, and in particular threshold pool mixes, are a building block of anonymous communications systems. These are nodes that receive, store, reorder and delay messages in batches. However, the anonymity gained from the statistical difficulty to link incoming and outgoing messages comes at the expense of introducing a potentially costly delay in the delivery of those messages. In this paper we address the design of such mixes in a systematic fashion, by defining quantitative measures of both anonymity and delay, and by mathematically formalizing practical design decisions as a multiobjective optimization problem. Our extensive theoretical analysis finds the optimal mix parametrization and characterizes the optimal trade-off between the contrasting aspects of anonymity and delay, for two information-theoretic measures of anonymity. Experimental results show that mix optimization may lead to substantial delay reductions for a desirable level of anonymity.