Abstract
An improvement over the previously known disclosure attack is presented that allows, using statistical methods, to effectively deanonymize users of a mix system. Furthermore the statistical disclosure attack is computationally efficient, and the conditions for it to be possible and accurate are much better understood. The new attack can be generalized easily to a variety of anonymity systems beyond mix networks.
The original version of this chapter was revised: The copyright line was incorrect. This has been corrected. The Erratum to this chapter is available at DOI: 10.1007/978-0-387-35691-4_52
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© 2003 IFIP International Federation for Information Processing
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Danezis, G. (2003). Statistical Disclosure Attacks. In: Gritzalis, D., De Capitani di Vimercati, S., Samarati, P., Katsikas, S. (eds) Security and Privacy in the Age of Uncertainty. SEC 2003. IFIP — The International Federation for Information Processing, vol 122. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-35691-4_40
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DOI: https://doi.org/10.1007/978-0-387-35691-4_40
Publisher Name: Springer, Boston, MA
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