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Detecting Traffic Snooping in Tor Using Decoys

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Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 6961))

Abstract

Anonymous communication networks like Tor partially protect the confidentiality of their users’ traffic by encrypting all intra-overlay communication. However, when the relayed traffic reaches the boundaries of the overlay network towards its actual destination, the original user traffic is inevitably exposed. At this point, unless end-to-end encryption is used, sensitive user data can be snooped by a malicious or compromised exit node, or by any other rogue network entity on the path towards the actual destination.

We explore the use of decoy traffic for the detection of traffic interception on anonymous proxying systems. Our approach is based on the injection of traffic that exposes bait credentials for decoy services that require user authentication. Our aim is to entice prospective eavesdroppers to access decoy accounts on servers under our control using the intercepted credentials. We have deployed our prototype implementation in the Tor network using decoy IMAP and SMTP servers. During the course of ten months, our system detected ten cases of traffic interception that involved ten different Tor exit nodes. We provide a detailed analysis of the detected incidents, discuss potential improvements to our system, and outline how our approach can be extended for the detection of HTTP session hijacking attacks.

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Robin Sommer Davide Balzarotti Gregor Maier

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© 2011 Springer-Verlag Berlin Heidelberg

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Chakravarty, S., Portokalidis, G., Polychronakis, M., Keromytis, A.D. (2011). Detecting Traffic Snooping in Tor Using Decoys. In: Sommer, R., Balzarotti, D., Maier, G. (eds) Recent Advances in Intrusion Detection. RAID 2011. Lecture Notes in Computer Science, vol 6961. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23644-0_12

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  • DOI: https://doi.org/10.1007/978-3-642-23644-0_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23643-3

  • Online ISBN: 978-3-642-23644-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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