Unmixing Mix Traffic
نویسندگان
چکیده
We apply blind source separation techniques from statistical signal processing to separate the traffic in a mix network into either individual flows or groups of flows. This separation requires no a priori information about the individual flows. As a result, unlinkability can be compromised without ever observing individual flows. Our experiments show that this attack is effective and scalable. By correlating separated groups of flows across nodes, a passive attacker can get an accurate traffic map of the mix network. We use a non-trivial network to show that the combined attack works. The experiments also show that multicast traffic can be dangerous for anonymity networks.
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