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Website Fingerprinting: Attacking Popular Privacy Enhancing Technologies with the Multinomial Naïve-Bayes Classifier

Herrmann, Dominik, Wendolsky, Rolf and Federrath, Hannes (2009) Website Fingerprinting: Attacking Popular Privacy Enhancing Technologies with the Multinomial Naïve-Bayes Classifier. In: CCSW '09: ACM Workshop on Cloud Computing Security, 13.11.2009, Chicago, Illinois, USA.

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Date of publication of this fulltext: 08 Jan 2010 08:23

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Abstract

Privacy enhancing technologies like OpenSSL, OpenVPN or Tor establish an encrypted tunnel that enables users to hide content and addresses of requested websites from external observers This protection is endangered by local traffic analysis attacks that allow an external, passive attacker between the PET system and the user to uncover the identity of the requested sites. However, existing ...

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Item type:Conference or workshop item (Paper)
Date:13 November 2009
Additional Information (public):erschienen: CCSW '09: Proceedings of the 2009 ACM workshop on Cloud computing security, ACM, New York, NY, 2009. ISBN: 978-1-60558-784-4
Institutions:Business, Economics and Information Systems > Institut für Wirtschaftsinformatik > Alumni or Retired Professors > Lehrstuhl für Wirtschaftsinformatik IV - Management der Informationssicherheit (Prof. Dr.-Ing. Hannes Federrath)
Identification Number:
ValueType
http://doi.acm.org/10.1145/1655008.1655013DOI
Related URLs:
URLURL Type
http://portal.acm.org/citation.cfm?doid=1655008.1655013Publisher
Keywords:forensics, low-latency anonymity, text mining, traffic analysis
Dewey Decimal Classification:000 Computer science, information & general works > 004 Computer science
Status:Published
Refereed:Yes, this version has been refereed
Created at the University of Regensburg:Yes
Item ID:11919
Owner only: item control page

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