Affiliation:
1. Yale University
2. Yale University, University of Texas at Austin, and U.S. Naval Research Laboratory
3. U.S. Naval Research Laboratory
Abstract
We perform a probabilistic analysis of onion routing. The analysis is presented in a black-box model of anonymous communication in the Universally Composable (UC) framework that abstracts the essential properties of onion routing in the presence of an active adversary who controls a portion of the network and knows all a priori distributions on user choices of destination. Our results quantify how much the adversary can gain in identifying users by exploiting knowledge of their probabilistic behavior. In particular, we show that, in the limit as the network gets large, a user
u
's anonymity is worst either when the other users always choose the destination
u
is least likely to visit or when the other users always choose the destination
u
chooses. This worst-case anonymity with an adversary that controls a fraction
b
of the routers is shown to be comparable to the best-case anonymity against an adversary that controls a fraction √
b
.
Funder
National Science Foundation
Army Research Office
United States-Israel Binational Science Foundation
Publisher
Association for Computing Machinery (ACM)
Subject
Safety, Risk, Reliability and Quality,General Computer Science
Cited by
29 articles.
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