Touching from a distance: website fingerprinting attacks and defenses

By Xiang Cai, Xin Cheng Zhang, Brijesh Joshi, Rob Johnson. 2012

469 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Signal Processing

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Citations in the corpus

Peek-a-boo: i see your smart home activities, even encrypted! (2018, background): “Not only identification attacks, but also the countermeasures have been studied in several studies [10, 19].”
Deep Fingerprinting: Undermining Website Fingerprinting Defenses with Deep Learning (2018, background): “There is research that has attempted to fingerprint pages that are linked from the homepage [8], but virtually all studies on website fingerprinting train and test the attacks on home pages.”
Users get routed: traffic correlation on tor by realistic adversaries (2013, background): “In this paper, we do not consider circuit clogging, network latency, or application 1 or other attacks against Tor (cf. [2, 5, 8, 14, 18, 24, 28]).”
A Systematic Approach to Developing and Evaluating Website Fingerprinting Defenses (2014, methodology): “We then use the new evaluation techniques described above to evaluate Tamaraw.”
Improved website fingerprinting on Tor (2013, methodology): “Cai et al. showed that this method was effective.”
Robust Smartphone App Identification via Encrypted Network Traffic Analysis (2017, background): “More recently, Cai et al. [19] presented a web page ﬁngerprinting attack and showed its effectiveness despite trafﬁc analysis countermeasures (e.g., HTTPOS).”
A Critical Evaluation of Website Fingerprinting Attacks (2014, methodology): “Some authors have also evaluated their classifiers in an open-world scenario [3, 23, 32], where there is a set of k target pages being monitored but the user is allowed to visit pages that are not in that set.”
Circuit Fingerprinting Attacks: Passive Deanonymization of Tor Hidden Services (2015, background): “Previous WF attacks assumed that the adversary is able to eliminate noisy background traffic [10, 35, 36].”
k-fingerprinting: A Robust Scalable Website Fingerprinting Technique (2015, methodology): “[7] modified the kernel in Panchenko et al.”
AppScanner: Automatic Fingerprinting of Smartphone Apps from Encrypted Network Traffic (2016, background): “More recently, Cai et al. [14] presented a web page ﬁngerprinting attack and showed its effectiveness despite trafﬁc analysis countermeasures (e.g., HTTPOS).”
Effective Attacks and Provable Defenses for Website Fingerprinting (2014, methodology): “Most previous defenses have been shown to fail against more advanced attacks [4, 6, 15]; this is because they were evaluated only against specific attacks, with no notion of provable effectiveness (against all possible attacks).”
Automated Website Fingerprinting through Deep Learning (2017, unknown): “First, Cai et al. [7] used an SVM with their custom kernel based on an edit-distance and achieved more than 86% accuracy for 100 sites.”
Website Fingerprinting at Internet Scale (2016, background): “pointed out several disadvantages of this approach [5]: besides a high overhead in bandwidth and time, BuFLO may reveal the total transmission size under certain conditions and further is not able to adapt for congestion.”
MemGuard: Defending against Black-Box Membership Inference Attacks via Adversarial Examples (2019, background): “…than membership inference attacks, many other attacks rely on machine learning classifiers, e.g., attribute inference attacks [11, 17, 28], website fingerprinting attacks [7, 22, 29, 46, 67], side-channel attacks [73], location attacks [5, 45, 52, 72], and author identification attacks [8, 41].”