Measuring Relationship Anonymity in Mix Networks. Shmatikov, V. & Wang, M. October 2006. ![Measuring Relationship Anonymity in Mix Networks [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Many applications of mix networks such as anonymousWeb browsing require relationship anonymity: it should be hard for the attacker to determine who is communicating with whom. Conventional methods for measuring anonymity, however, focus on sender anonymity instead. Sender anonymity guarantees that it is difficult for the attacker to determine the origin of any given message exiting the mix network, but this may not be sufficient to ensure relationship anonymity. Even if the attacker cannot identify the origin of messages arriving to some destination, relationship anonymity will fail if he can determine with high probability that at least one of the messages originated from a particular sender, without necessarily being able to recognize this message among others. We give a formal definition and a calculation methodology for relationship anonymity. Our techniques are similar to those used for sender anonymity, but, unlike sender anonymity, relationship anonymity is sensitive to the distribution of message destinations. In particular, Zipfian distributions with skew values characteristic of Web browsing provide especially poor relationship anonymity. Our methodology takes route selection algorithms into account, and incorporates information-theoretic metrics such as entropy and min-entropy. We illustrate our methodology by calculating relationship anonymity in several simulated mix networks.
@conference {ShWa-Relationship,
title = {Measuring Relationship Anonymity in Mix Networks},
booktitle = {Proceedings of the Workshop on Privacy in the Electronic Society (WPES 2006)},
year = {2006},
month = {October},
publisher = {ACM New York, NY, USA},
organization = {ACM New York, NY, USA},
abstract = {Many applications of mix networks such as anonymousWeb browsing require relationship anonymity: it should be hard for the attacker to determine who is communicating with whom. Conventional methods for measuring anonymity, however, focus on sender anonymity instead. Sender anonymity guarantees that it is difficult for the attacker to determine the origin of any given message exiting the mix network, but this may not be sufficient to ensure relationship anonymity. Even if the attacker cannot identify the origin of messages arriving to some destination, relationship anonymity will fail if he can determine with high probability that at least one of the messages originated from a particular sender, without necessarily being able to recognize this message among others. We give a formal definition and a calculation methodology for relationship anonymity. Our techniques are similar to those used for sender anonymity, but, unlike sender anonymity, relationship anonymity is sensitive to the distribution of message destinations. In particular, Zipfian distributions with skew values characteristic of Web browsing provide especially poor relationship anonymity. Our methodology takes route selection algorithms into account, and incorporates information-theoretic metrics such as entropy and min-entropy. We illustrate our methodology by calculating relationship anonymity in several simulated mix networks.
},
keywords = {anonymity, privacy},
isbn = {1-59593-556-8},
doi = {10.1145/1179601.1179611},
url = {http://portal.acm.org/citation.cfm?id=1179611},
author = {Vitaly Shmatikov and Ming-Hsui Wang}
}
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