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<b>URL:</b>
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<a href="http://dcs.ics.forth.gr/Activities/papers/2006.CMS.trace-anonymization.pdf">http://dcs.ics.forth.gr/Activities/papers/2006.CMS.trace-anonymization.pdf</a>
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<b>ENTRY DATE:</b>
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2008-06-16


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<b>ABSTRACT:</b>
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Networking researchers and engineers rely on network packet traces for
understanding network behavior, developing models, and evaluating
network p erformance. Although the bulk of published packet traces
implement a form of address anonymization to hide sensitive information,
it has been unclear if such anonymization techniques are sufficient to
address the privacy concerns of users and organizations.  In this pap er
we attempt to quantify the risks of publishing anonymized packet
traces. In particular, we examine whether statistical identification
techniques can be used to uncover the identities of users and their
surfing activities from anonymized packet traces. Our results show that
such techniques can be used by any Web server that is itself present in
the packet trace and has suficient resources to map out and keep track
of the content of popular Web sites to obtain information on the
network-wide browsing b ehavior of its clients. Furthermore, we discuss
how scan sequences identified in the trace can easily reveal the mapping
from anonymized to real IP addresses.




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