175 research outputs found
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
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