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Probabilistic treatment of MIXes to hamper traffic analysis
Written by:
Dakshi Agrawal,
Dogan Kesdogan, and Stefan Penz.
Citation:
Proceedings of IEEE 2003 Symposium on Security and Privacy, pages 16-27, May 2003.
Copyright © (2003) by IEEE. Permission to make digital or
hard copies of part or all of this work for personal or classroom use
is granted without fee provided that copies are not made or distributed
for profit. To copy otherwise, to republish, to post on servers, or to
redistribute to lists, requires prior specific permission and/or a fee.
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. 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)
'weak operational modes' of the MIXes and thus to protect users against
a traffic analysis by the disclosure attack.
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