  The Tor anonymity network has been shown vulnerable to traffic analysis
attacks by autonomous systems and Internet exchanges, which can observe
different overlay hops belonging to the same circuit. We aim to determine
whether network path prediction techniques provide an accurate picture of the
threat from such adversaries, and whether they can be used to avoid this
threat. We perform a measurement study by running traceroutes from Tor relays
to destinations around the Internet. We use the data to evaluate the accuracy
of the autonomous systems and Internet exchanges that are predicted to appear
on the path using state-of-the-art path inference techniques; we also consider
the impact that prediction errors have on Tor security, and whether it is
possible to produce a useful overestimate that does not miss important threats.
Finally, we evaluate the possibility of using these predictions to actively
avoid AS and IX adversaries and the challenges this creates for the design of
Tor.
