Bayesian traffic analysis
5 August 2009
In the last year, we have been developping a set of systematic techniques to analyse anonymity systems, to perform traffic analysis. These cast the problem of traffic analysis as a Bayesian inference problem, where the adversay observes some traces, according to a threat model, and then has to infer the hidden state of the system, that is equivalent to tracing who is talking to whom.
So far we have looked at the analysis of mix networks, the analysis of Crowds, and a Bayesian approach to long term intersection attacks. The papers describing each of these are available online:
- Carmela Troncoso and George Danezis.
The Bayesian Traffic Analysis of Mix Networks. (Draft)
ACM CCS 2009, Chicago, USA.
- George Danezis, Claudia Diaz, Emilia Kasper, and Carmela Troncoso.
The wisdom of Crowds: attacks and optimal constructions.
ESORICS 2009, St Malo, France.
- George Danezis and Carmela Troncoso.
Vida: How to use Bayesian inference to de-anonymize persistent communications.
PETS 2009, Seattle, USA.