Guard Sets for Onion Routing

“Entry” guards protect the Tor onion routing system from variants of the “predecessor” attack, that would allow an adversary with control of a fraction of routers to eventually de-anonymize some users. Research has however shown the three guard scheme has drawbacks and Dingledine et al. proposed in 2014 for each user to have a single long-term guard. We first show that such a guard selection strategy would be optimal if the Tor network was failure-free and static. However under realistic failure conditions the one guard proposal still suffers from the classic fingerprinting attacks, uniquely identifying users. Furthermore, under dynamic network conditions using single guards offer smaller anonymity sets to users of fresh guards. We propose and analyze an alternative guard selection scheme by way of grouping guards together to form shared guard sets. We compare the security and performance of guard sets with the three guard scheme and the one guard proposal. We show guard sets do provide increased resistance to a number of attacks, while foreseeing no significant degradation in performance or bandwidth utilization

Defending Tor from Network Adversaries: A Case Study of Network Path Prediction

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

Representing Network Trust and Using It to Improve Anonymous Communication

Motivated by the effectiveness of correlation attacks against Tor, the censorship arms race, and observations of malicious relays in Tor, we propose that Tor users capture their trust in network elements using probability distributions over the sets of elements observed by network adversaries. We present a modular system that allows users to efficiently and conveniently create such distributions and use them to improve their security. The major components of this system are (i) an ontology of network-element types that represents the main threats to and vulnerabilities of anonymous communication over Tor, (ii) a formal language that allows users to naturally express trust beliefs about network elements, and (iii) a conversion procedure that takes the ontology, public information about the network, and user beliefs written in the trust language and produce a Bayesian Belief Network that represents the probability distribution in a way that is concise and easily sampleable. We also present preliminary experimental results that show the distribution produced by our system can improve security when employed by users; further improvement is seen when the system is employed by both users and services.Comment: 24 pages; talk to be presented at HotPETs 201