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Realistic Cover Traffic to Mitigate Website Fingerprinting Attacks

机译:实际的掩护流量以缓解网站指纹攻击

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Website fingerprinting attacks have been shown to be able to predict the website visited even if the network connection is encrypted and anonymized. These attacks have achieved accuracies as high as 92%. Mitigations to these attacks are using cover/decoy network traffic to add noise, padding to ensure all the network packets are the same size, and introducing network delays to confuse an adversary. Although these mitigations have been shown to be effective, reducing the accuracy to 10%, the overhead is very high. The latency overhead is above 100% and the bandwidth overhead is at least 40%. We introduce a new realistic cover traffic algorithm, based on a user's previous network traffic, to mitigate website fingerprinting attacks. In simulations, our algorithm reduces the accuracy of attacks to 14% with zero latency overhead and about 20% bandwidth overhead.
机译:已经证明,即使网络连接已加密和匿名,网站指纹攻击也能够预测访问的网站。这些攻击的准确率高达92%。缓解这些攻击的方法是使用掩盖/诱饵网络流量增加噪声,填充以确保所有网络数据包的大小相同,并引入网络延迟以使对手感到困惑。尽管这些缓解措施已被证明是有效的,但将精度降低到10%,但是开销却非常高。延迟开销超过100%,带宽开销至少为40%。我们基于用户以前的网络流量引入了一种新的现实的覆盖流量算法,以缓解网站指纹攻击。在仿真中,我们的算法将攻击的准确性降低到14%,而零延迟开销和大约20%的带宽开销。

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