The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Touching from a distance: website fingerprinting attacks and defenses
Abstract
We present a novel web page fingerprinting attack that is able to defeat several recently proposed defenses against traffic analysis attacks, including the application-level defenses HTTPOS and randomized pipelining over Tor. Regardless of the defense scheme, our attack was able to guess which of 100 web pages a victim was visiting at least 50% of the time and, with some defenses, over 90% of the time. Our attack is based on a simple model of network behavior and out-performs previously proposed ad hoc attacks. We then build a web site fingerprinting attack that is able to identify whether a victim is visiting a particular web site with over 90% accuracy in our experiments.
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Citations
Cites
The Nature of Statistical Learning Theory
Vapnik, V. N. (1995) · doi:10.1007/978-1-4757-2440-0 · Cited by 39,138
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
“More recently, Cai et al. [19] presented a web page fingerprinting attack and showed its effectiveness despite traffic analysis countermeasures (e.g., HTTPOS).”
BackgroundA 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
- Cai, X., Zhang, X. C., Joshi, B., & Johnson, R.
- Venue
- Proceedings of the 2012 ACM conference on Computer and communications security
- Publisher
- ACM
- Published
- 2012-10-16
- Pages
- 605-616
- ISSN
- 1543-7221 (ISSN-L)
- OpenAlex
- W2170085959
- Cited by
- 394
- References
- 2
- FWCI
- 14.77
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Touching from a distance: website fingerprinting attacks and defenses. https://app.cochat.ai/papers/10.1145/2382196.2382260
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- Cai, X., Zhang, X. C., Joshi, B., & Johnson, R. (2012). Touching from a distance: website fingerprinting attacks and defenses. Proceedings of the 2012 ACM conference on Computer and communications security. https://doi.org/10.1145/2382196.2382260
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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