Title
Measuring and mitigating AS-level adversaries against Tor
Abstract
The popularity of Tor as an anonymity system has made it a popular target for a variety of attacks. We focus on traffic correlation attacks, which are no longer solely in the realm of academic research with recent revelations about the NSA and GCHQ actively working to implement them in practice. Our first contribution is an empirical study that allows us to gain a high fidelity snapshot of the threat of traffic correlation attacks in the wild. We find that up to 40% of all circuits created by Tor are vulnerable to attacks by traffic correlation from Autonomous System (AS)-level adversaries, 42% from colluding AS-level adversaries, and 85% from state-level adversaries. In addition, we find that in some regions (notably, China and Iran) there exist many cases where over 95% of all possible circuits are vulnerable to correlation attacks, emphasizing the need for AS-aware relay-selection. To mitigate the threat of such attacks, we build Astoria--an AS-aware Tor client. Astoria leverages recent developments in network measurement to perform path-prediction and intelligent relay selection. Astoria reduces the number of vulnerable circuits to 2% against AS-level adversaries, under 5% against colluding AS-level adversaries, and 25% against state-level adversaries. In addition, Astoria load balances across the Tor network so as to not overload any set of relays.
Year
Venue
Field
2015
NDSS
Internet privacy,Network measurement,Computer science,Computer security,Popularity,Autonomous system (mathematics),Correlation attack,Anonymity,Relay,Empirical research
DocType
Volume
Citations 
Journal
abs/1505.05173
9
PageRank 
References 
Authors
0.50
19
5
Name
Order
Citations
PageRank
Rishab Nithyanand124216.39
Oleksii Starov21029.31
Adva Zair3111.23
Phillipa Gill41504114.56
Michael Schapira5112279.89