SoK: A Critical Evaluation of Efficient Website Fingerprinting Defenses
SoK: A Critical Evaluation of Efficient Website Fingerprinting Defenses
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DOI：
10.1109/sp46215.2023.10179289
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发表时间：
2023-05
期刊：
影响因子：
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通讯作者：
Nate Mathews;James K. Holland;Se Eun Oh;Mohammad Saidur Rahman;Nicholas Hopper;M. Wright
中科院分区：
文献类型：
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作者：
Nate Mathews;James K. Holland;Se Eun Oh;Mohammad Saidur Rahman;Nicholas Hopper;M. Wright
最近的网站指纹攻击已被证明可以通过Tor实现非常高的性能。这些攻击允许对手通过简单地窃听加密通信来推断Tor用户访问过的网站。因此，这激发了许多防御策略的发展，这些策略通过添加虚拟数据包和/或延迟来混淆流量。最近提出的许多建议的有效性和实用性尚待详细审查。在这项研究中，我们重新评估了最近的九项防御提案，这些提案声称使用最新的基于深度学习的攻击提供足够的安全性和低开销。此外，我们评估了在Tor当前范围内实施这些防御的可行性。为此，我们还提供了DynaFlow防御的第一个网络实现，以更好地评估其现实世界的效用。
Recent website fingerprinting attacks have been shown to achieve very high performance against traffic through Tor. These attacks allow an adversary to deduce the website a Tor user has visited by simply eavesdropping on the encrypted communication. This has consequently motivated the development of many defense strategies that obfuscate traffic through the addition of dummy packets and/or delays. The efficacy and practicality of many of these recent proposals have yet to be scrutinized in detail. In this study, we re-evaluate nine recent defense proposals that claim to provide adequate security with low-overheads using the latest Deep Learning-based attacks. Furthermore, we assess the feasibility of implementing these defenses within the current confines of Tor. To this end, we additionally provide the first on-network implementation of the DynaFlow defense to better assess its real-world utility.