Probabilistic Treatment of MIXes to Hamper Traffic Analysis. Agrawal, D., Kesdogan, D., & Penz, S. 05/2003 2003. ![Probabilistic Treatment of MIXes to Hamper Traffic Analysis [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper abstract bibtex The goal of anonymity providing techniques is to preserve the privacy of users, who has communicated with whom, for how long, and from which location, by hiding traffic information. This is accomplished by organizing additional traffic to conceal particular communication relationships and by embedding the sender and receiver of a message in their respective anonymity sets. If the number of overall participants is greater than the size of the anonymity set and if the anonymity set changes with time due to unsynchronized participants, then the anonymity technique becomes prone to traffic analysis attacks. In this paper, we are interested in the statistical properties of the disclosure attack, a newly suggested traffic analysis attack on the MIXes. Our goal is to provide analytical estimates of the number of observations required by the disclosure attack and to identify fundamental (but avoidable) \textquoteleftweak operational modes\textquoteright of the MIXes and thus to protect users against a traffic analysis by the disclosure attack.
@conference {agrawal03,
title = {Probabilistic Treatment of MIXes to Hamper Traffic Analysis},
booktitle = {Proceedings of the 2003 IEEE Symposium on Security and Privacy},
year = {2003},
month = {05/2003},
pages = {16{\textendash}27},
publisher = {IEEE Computer Society Washington, DC, USA},
organization = {IEEE Computer Society Washington, DC, USA},
abstract = {The goal of anonymity providing techniques is to preserve the privacy of users, who has communicated with whom, for how long, and from which location, by hiding traffic information. This is accomplished by organizing additional traffic to conceal particular communication relationships and by embedding the sender and receiver of a message in their respective anonymity sets. If the number of overall participants is greater than the size of the anonymity set and if the anonymity set changes with time due to unsynchronized participants, then the anonymity technique becomes prone to traffic analysis attacks. In this paper, we are interested in the statistical properties of the disclosure attack, a newly suggested traffic analysis attack on the MIXes. Our goal is to provide analytical estimates of the number of observations required by the disclosure attack and to identify fundamental (but avoidable) {\textquoteleft}weak operational modes{\textquoteright} of the MIXes and thus to protect users against a traffic analysis by the disclosure attack.},
keywords = {anonymity measurement, mix, traffic analysis},
isbn = {0-7695-1940-7},
url = {http://portal.acm.org/citation.cfm?id=829515.830557},
author = {Dakshi Agrawal and Dogan Kesdogan and Stefan Penz}
}
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