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Onions in the Crosshairs: When The Man really is out to get you

Published:30 October 2017Publication History

ABSTRACT

We introduce and investigate targeting adversaries who selectively attack users of Tor or other secure-communication networks. We argue that attacks by such adversaries are more realistic and more significant threats to those most relying on Tor's protection than are attacks in prior analyses of Tor security. Previous research and Tor design decisions have focused on protecting against adversaries who are equally interested in any user of the network. Our adversaries selectively target users - e.g., those who visit a particular website or chat on a particular private channel - and essentially disregard Tor users other than these. We investigate three example cases where particular users might be targeted: a cabal conducting meetings using MTor, a published Tor multicast protocol; a cabal meeting on a private IRC channel; and users visiting a particular .onion website. In general for our adversaries, compromise is much faster and provides more feedback and possibilities for adaptation than do attacks examined in prior work. We also discuss selection of websites for targeting of their users based on the distribution across users of site activity. We describe adversaries attempting to learn the size of either a cabal meeting online or a set of sufficiently active visitors to a targeted site, and we describe adversaries attempting to identify guards of each targeted user. We compare the threat of targeting adversaries versus previously considered adversaries, and we briefly sketch possible countermeasures for resisting targeting adversaries.

References

  1. Nicola Accettura, Giovanni Neglia, and Luigi Alfredo Grieco. The capture-recapture approach for population estimation in computer networks. Computer Networks, 89:107--122, 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. J. Appelbaum and A. Muffett. The ".onion" special-use domain name. https://tools.ietf.org/html/rfc7686, 2015.Google ScholarGoogle Scholar
  3. Alex Biryukov, Ivan Pustogarov, and Ralf-Philipp Weinmann. Trawling for Tor hidden services: Detection, measurement, deanonymization. Proc. IEEE SP, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. George Danezis and Paul Syverson. Bridging and fingerprinting: Epistemic attacks on route selection. Proc. PETS, pages 151--166, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Roger Dingledine. The lifecycle of a new relay. https://blog.torproject.org/blog/lifecycle-of-a-new-relay, September 2013.Google ScholarGoogle Scholar
  6. Roger Dingledine, Nick Mathewson, and Paul Syverson. Tor: The Second-Generation Onion Router. Proc. USENIX Security Symposium, 2004. Google ScholarGoogle ScholarCross RefCross Ref
  7. Nick Feamster and Roger Dingledine. Location diversity in anonymity networks. Proc. ACM WPES, pages 66--76, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. David Goulet and George Kadianakis. Random number generation during Tor voting (Tor proposal #250). https://gitweb.torproject.org/torspec.git/tree/proposals/250-commit-reveal-consensus.txt, August 2015.Google ScholarGoogle Scholar
  9. Berk Gulmezoglu, Andreas Zank, Thomas Eisenbarth, and Berk Sunar. PerfWeb: How to Violate Web Privacy with Hardware Performance Events. Proc. ESORICS, Part II, pages 80--97, 2017. Google ScholarGoogle ScholarCross RefCross Ref
  10. Andrew Hintz. Fingerprinting websites using traffic analysis. Privacy Enhancing Technologies: Second International Workshop (PET), pages 171--178, 2002.Google ScholarGoogle Scholar
  11. Nicholas Hopper, Eugene Y. Vasserman, and Eric Chan-Tin. How much anonymity does network latency leak? Proc. ACM CCS, pages 82--91, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Aaron D. Jaggard, Aaron Johnson, Sarah Cortes, Paul Syverson, and Joan Feigenbaum. 20,000 in league under the sea: Anonymous communication, trust, MLATs, and undersea cables. Proc. Privacy Enhancing Technologies, 2015(1):4--24, April 2015. Google ScholarGoogle ScholarCross RefCross Ref
  13. Aaron D. Jaggard and Paul Syverson. Onions in the crosshairs: When The Man really is out to get you, 2017. https://arxiv.org/abs/1706.10292.Google ScholarGoogle Scholar
  14. Rob Jansen, Florian Tschorsch, Aaron Johnson, and Björn Scheuermann. The sniper attack: Anonymously deanonymizing and disabling the Tor network. Proc. NDSS, 2014. Google ScholarGoogle ScholarCross RefCross Ref
  15. Aaron Johnson. Tor Path Simulator code. https://github.com/torps/torps.Google ScholarGoogle Scholar
  16. Aaron Johnson and Paul Syverson. More anonymous onion routing through trust. Proc. IEEE CSF, pages 3--12, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Aaron Johnson, Paul Syverson, Roger Dingledine, and Nick Mathewson. Trust-based anonymous communication: Adversary models and routing algorithms. Proc. ACM CCS, pages 175--186, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Aaron Johnson, Chris Wacek, Rob Jansen, Micah Sherr, and Paul Syverson. Users get routed: Traffic correlation on Tor by realistic adversaries. Proc. ACM CCS, pages 337--348, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Marc Juarez, Rob Jansen, Rafael Galvez, Tariq Elahi, Claudia Diaz, and Matthew Wright. Poster: Fingerprinting hidden service circuits from a Tor middle relay. Proc. IEEE SP, 2017.Google ScholarGoogle Scholar
  20. George Kadianakis and Mike Perry. Defending against guard discovery attacks using vanguards (Tor proposal #247). https://gitweb.torproject.org/torspec.git/tree/proposals/247-hs-guard-discovery.txt, July 2015.Google ScholarGoogle Scholar
  21. Dong Lin, Micah Sherr, and Boon Thau Loo. Scalable and anonymous group communication with MTor. Proc. Privacy Enhancing Technologies, 2016(2):22--39, June 2016.Google ScholarGoogle ScholarCross RefCross Ref
  22. Nick Mathewson. Next-generation hidden services in Tor, (Tor proposal #224). https://gitweb.torproject.org/torspec.git/tree/proposals/224-rend-spec-ng.txt, November 2013.Google ScholarGoogle Scholar
  23. Nick Mathewson. Some thoughts on hidden services. https://blog.torproject.org/blog/some-thoughts-hidden-services, December 2014.Google ScholarGoogle Scholar
  24. Rafail Ostrovsky and Moti Yung. How to withstand mobile virus attacks. Proc. ACM PODC, pages 51--59, 1991.Google ScholarGoogle Scholar
  25. Lasse Øverlier and Paul Syverson. Locating hidden servers. Proc. IEEE SP, pages 100--114, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Gareth Owen and Nick Savage. The Tor dark net. Paper Series: No. 20 20, Global Commission on Internet Governance, September 2015.Google ScholarGoogle Scholar
  27. Personal communication.Google ScholarGoogle Scholar
  28. Michael Reiter and Aviel Rubin. Crowds: Anonymity for web transactions. ACM Trans. Information and System Security (TISSEC), 1(1):66--92, 1998. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. Yixin Sun, Anne Edmundson, Laurent Vanbever, Oscar Li, Jennifer Rexford, Mung Chiang, and Prateek Mittal. RAPTOR: Routing attacks on privacy in Tor. Proc. USENIX Security, 2015.Google ScholarGoogle Scholar
  30. Paul Syverson, Gene Tsudik, Michael Reed, and Carl Landwehr. Towards an analysis of onion routing security. Proc. International Workshop on Designing Privacy Enhancing Technologies: Design Issues in Anonymity and Unobservability, pages 96--114, 2001. Google ScholarGoogle ScholarCross RefCross Ref
  31. Who uses Tor. https://www.torproject.org/about/torusers.html. Accessed February 2017.Google ScholarGoogle Scholar
  32. Tor metrics portal. https://metrics.torproject.org/.Google ScholarGoogle Scholar
  33. Tor network size. https://metrics.torproject.org/networksize.html.Google ScholarGoogle Scholar
  34. The Tor Project. https://www.torproject.org/.Google ScholarGoogle Scholar
  35. Ding Wang, Zijian Zhang, Ping Wang, Jeff Yan, and Xinyi Huang. Targeted online password guessing: An underestimated threat. Proc. ACM CCS, pages 1242--1254, 2016. Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. Tao Wang and Ian Goldberg. On realistically attacking Tor with website fingerprinting. Proc. Privacy Enhancing Technologies, 2016(4):21--36, October 2016.Google ScholarGoogle ScholarCross RefCross Ref
  37. Tim Wilson-Brown, John Brooks, Aaron Johnson, Rob Jansen, George Kadianakis, Paul Syverson, and Roger Dingledine. Rendezvous single onion services, (Tor proposal #260). https://gitweb.torproject.org/torspec.git/tree/proposals/260-rend-single-onion.txt, 2015.Google ScholarGoogle Scholar
  38. Matthew Wright, Micah Adler, Brian Neil Levine, and Clay Shields. Defending anonymous communication against passive logging attacks. Proc. IEEE SP, pages 28--43, 2003. Google ScholarGoogle ScholarCross RefCross Ref

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      • Published in

        cover image ACM Conferences
        WPES '17: Proceedings of the 2017 on Workshop on Privacy in the Electronic Society
        October 2017
        184 pages
        ISBN:9781450351751
        DOI:10.1145/3139550

        Copyright © 2017 Public Domain

        This paper is authored by an employee(s) of the United States Government and is in the public domain. Non-exclusive copying or redistribution is allowed, provided that the article citation is given and the authors and agency are clearly identified as its source.

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 30 October 2017

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        WPES '17 Paper Acceptance Rate14of56submissions,25%Overall Acceptance Rate106of355submissions,30%

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