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Measuring relationship anonymity in mix networks
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Source Workshop On Privacy In The Electronic Society archive
Proceedings of the 5th ACM workshop on Privacy in electronic society table of contents
Alexandria, Virginia, USA
SESSION: Short papers table of contents
Pages: 59 - 62  
Year of Publication: 2006
ISBN:1-59593-556-8
Authors
Vitaly Shmatikov  The University of Texas at Austin
Ming-Hsiu Wang  The University of Texas at Austin
Sponsors
SIGSAC: ACM Special Interest Group on Security, Audit, and Control
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 6,   Downloads (12 Months): 37,   Citation Count: 2
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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.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Vitaly Shmatikov: colleagues
Ming-Hsiu Wang: colleagues