# Towards Relations Between the Hitting-Set Attack and the Statistical Disclosure Attack

Abstract : The Minimal-Hitting-Set attack (HS-attack) is a well-known, provably optimal exact attack against the anonymity provided by Chaumian Mixes (Threshold-Mixes). This attack allows an attacker to identify the fixed set of communication partners of a given user by observing all messages sent and received by a Chaum Mix. In contrast to this, the Statistical Disclosure attack (SDA) provides a guess of that user’s contacts, based on statistical analyses of the observed message exchanges.We contribute the first closed formula that shows the influence of traffic distributions on the least number of observations of the Mix to complete the HS-attack. This measures when the Mix fails to hide a user’s partners, such that the user cannot plausibly deny the identified contacts. It reveals that the HS-attack requires asymptotically less observations to identify a user’s partners than the SDA, which guesses them with a given bias. This number of observations is $O\left(\frac{1}{p}\right)$ for the HS-attack and $O\left(\frac{1}{{p}^{2}}\right)$ for the SDA, where $p$ the probability that the attacked user contacts his least frequent partner.
Type de document :
Communication dans un congrès
Hannes Federrath; Dieter Gollmann. 30th IFIP International Information Security Conference (SEC), May 2015, Hamburg, Germany. IFIP Advances in Information and Communication Technology, AICT-455, pp.35-50, 2015, ICT Systems Security and Privacy Protection. 〈10.1007/978-3-319-18467-8_3〉
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Soumis le : mercredi 13 juillet 2016 - 10:51:00
Dernière modification le : lundi 18 juillet 2016 - 10:46:16

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### Citation

Dang Pham, Dogan Kesdogan. Towards Relations Between the Hitting-Set Attack and the Statistical Disclosure Attack. Hannes Federrath; Dieter Gollmann. 30th IFIP International Information Security Conference (SEC), May 2015, Hamburg, Germany. IFIP Advances in Information and Communication Technology, AICT-455, pp.35-50, 2015, ICT Systems Security and Privacy Protection. 〈10.1007/978-3-319-18467-8_3〉. 〈hal-01345094〉

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