The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Website fingerprinting: attacking popular privacy enhancing technologies with the multinomial naïve-bayes classifier
Open accessAbstract
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 proposals for such attacks are not practicable yet.
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Citations
Cites
Introduction to information retrieval
(2009) · Choice Reviews Online · doi:10.5860/choice.46-2715 · Cited by 12,278
Tor: The Second-Generation Onion Router
Dingledine, R., Mathewson, N., & Syverson, P. (2004) · doi:10.21236/ada465464 · Cited by 4,104
Statistical identification of encrypted Web browsing traffic
Sun, Q., Simon, D. R., Wang, Y.-M., Russell, W., Padmanabhan, V. N., & Qiu, L. (2005) · Proceedings 2002 IEEE Symposium on Security and Privacy · doi:10.1109/secpri.2002.1004359 · Cited by 377
Cited by
Website Fingerprinting at Internet Scale
Panchenko, A., Lanze, F., Zinnen, A., Henze, M., Pennekamp, J., Wehrle, K., & Engel, T. (2016) · Proceedings 2016 Network and Distributed System Security Symposium · doi:10.14722/ndss.2016.23477 · Cited by 645
Deep Fingerprinting: Undermining Website Fingerprinting Defenses with Deep Learning
Sirinam, P., Imani, M., Juarez, M., & Wright, M. (2018) · Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security · doi:10.1145/3243734.3243768 · Cited by 592
Robust Smartphone App Identification via Encrypted Network Traffic Analysis
Taylor, V. F., Spolaor, R., Conti, M., & Martinovic, I. (2018) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2017.2737970 · Cited by 439
“Subsequently, Herman et al. [17] outperformed Liberatore et al. by presenting a method that relies on common text mining techniques to the normalized frequency distribution of observable IP packet sizes.”
MethodA Critical Evaluation of Website Fingerprinting Attacks
Juarez, M., Afroz, S., Acar, G., Diaz, C., & Greenstadt, R. (2014) · Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security · doi:10.1145/2660267.2660368 · Cited by 327
A Survey on Encrypted Network Traffic Analysis Applications, Techniques, and Countermeasures
Papadogiannaki, E., & Ioannidis, S. (2022) · ACM Computing Surveys · doi:10.1145/3457904 · Cited by 281
Metadata
- Authors
- Herrmann, D., Wendolsky, R., & Federrath, H.
- Venue
- Proceedings of the 2009 ACM workshop on Cloud computing security
- Publisher
- ACM
- Published
- 2009-11-13
- Pages
- 31-42
- OpenAlex
- W2108217512
- Cited by
- 424
- References
- 3
- FWCI
- 7.29
- Type
- conference paper
- Language
- en
- Open access
- green
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- Herrmann, D., Wendolsky, R., & Federrath, H. (2009). Website fingerprinting: attacking popular privacy enhancing technologies with the multinomial naïve-bayes classifier. Proceedings of the 2009 ACM workshop on Cloud computing security. https://doi.org/10.1145/1655008.1655013
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
