Optimizing the design parameters of threshold pool mixes for anonymity and delay

Abstract

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. Mixes, 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.Postprint (published version

A Survey on Measuring Anonymity in Anonymous Communication Systems

“…In 2014, Monedero et al [75] found 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 showed that mix optimization may lead to substantial delay reductions for a desirable level of anonymity.…”

Filter design for delay-based anonymous communications

“…Fig- b) Distributed exponential mix. We want to build an exponential mix, i.e., a timed mix with d k = α(1 − α) k , which is optimal for some privacy metrics [3,4]. This is equivalent to a first-order IIR filter which we can implement easily in direct form, using a node that only delays messages until the end of a round (d = 1) and a switch that sends messages to an output with probability α, and to the other with probability 1 − α (Fig.…”

“…The design of the delya characteristic of an anonymous communication system has been studied in the literature with different privacy goals in mind [3,4,5]. In this work, we take over the work in [5], where the authors obtain the optimal delay characteristic against an eavesdropper with global vision of the network that tries to learn the average number of messages each sender sends to each receiver.…”

“…Finally, in Sect. 4 we give examples of how some properties of filter design can be used in the implementation of delay-based anonymous communications, and conclude in Sect. 5.…”

Mixnet optimization methods

“…3 Traffic analysis is a collection of statistical methods to make inferences from available metadata, in particular: a data transmission's source, destination, size and timing [13]. The traffic analysis of mixnets yields probabilistic information that describes the likelihood of input messages corresponding to outputs [11,19,31,44,46,47,[50][51][52]. This likelihood is greatly affected by the mixnet parameters, with some configurations providing significantly better protection from traffic analysis than others.…”