Website Fingerprinting Through the Cache Occupancy Channel and its Real World Practicality
Website Fingerprinting Through the Cache Occupancy Channel and its Real World Practicality
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DOI：
10.1109/tdsc.2020.2988369
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发表时间：
2020-04
影响因子：
7.3
通讯作者：
A. Shusterman;Zohar Avraham;Eliezer Croitoru;Yarden Haskal;Lachlan Kang;Dvir Levi;Yosef Meltser;Prateek Mittal;Yossi Oren;Y. Yarom
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文献类型：
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作者：
A. Shusterman;Zohar Avraham;Eliezer Croitoru;Yarden Haskal;Lachlan Kang;Dvir Levi;Yosef Meltser;Prateek Mittal;Yossi Oren;Y. Yarom
网站指纹攻击使用网络流量的统计分析来损害用户隐私。用于评估网站指纹攻击的经典攻击模型假设路径上的对手会观察用户计算机和网络之间传输的流量。在本文中，我们将研究一种不同的攻击模型，在这种模型中，攻击者将JavaScript代码发送到目标用户的计算机。这段代码会发起缓存旁路攻击，以识别正在浏览的其他网站。使用机器学习技术对缓存活动的痕迹进行分类，我们在开放世界和封闭世界模型中都实现了高分类精度。我们的攻击比基于网络的指纹响应缓存的影响更有抵抗力，并且对基于网络的防御和侧信道对策都有弹性。我们对攻击的几个方面进行了真实的评估，探索网站和浏览器随时间变化的影响，以及攻击者猜测目标用户计算机的软件和硬件配置的能力。为了防止基于缓存的网站指纹识别，必须为隐私敏感的浏览器和网站引入新的防御机制。我们研究了一种这样的机制，并表明它降低了攻击的有效性，并在Tor浏览器中使用时完全消除了它。
Website fingerprinting attacks use statistical analysis on network traffic to compromise user privacy. The classical attack model used to evaluate website fingerprinting attacks assumes an on-path adversary, who observes traffic traveling between the user's computer and the network. In this article we investigate a different attack model, in which the adversary sends JavaScript code to the target user's computer. This code mounts a cache side-channel attack to identify other websites being browsed. Using machine learning techniques to classify traces of cache activity, we achieve high classification accuracy in both the open-world and the closed-world models. Our attack is more resistant than network-based fingerprinting to the effects of response caching, and resilient both to network-based defenses and to side-channel countermeasures. We carry out a real-world evaluation of several aspects of our attack, exploring the impact of the changes in websites and browsers over time, as well as of the attacker's ability to guess the software and hardware configuration of the target user's computer. To protect against cache-based website fingerprinting, new defense mechanisms must be introduced to privacy-sensitive browsers and websites. We investigate one such mechanism, and show that it reduces the effectiveness of the attack and completely eliminates it when used in the Tor Browser.