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Efficient Web Browsing with Perfect Anonymity Using Page Prefetching

机译:使用页面预取功能以完美的匿名性进行有效的Web浏览

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Anonymous web browsing is a hot topic with many potential applications for privacy reasons. The current dominant strategy to achieve anonymity is packet padding with dummy packets as cover traffic. However, this method introduces extra bandwidth cost and extra delay. Therefore, it is not practical for anonymous web browsing applications. In order to solve this problem, we propose to use the predicted web pages that users are going to access as the cover traffic rather than dummy packets. Moreover, we defined anonymity level as a metric to measure anonymity degrees, and established a mathematical model for anonymity systems, and transformed the anonymous communication problem into an optimization problem. As a result, users can find tradeoffs among anonymity level and cost. With the proposed model, we can describe and compare our proposal and the previous schemas in a theoretical style. The preliminary experiments on the real data set showed the huge potential of the proposed strategy in terms of resource saving.
机译:出于隐私原因,匿名Web浏览是许多潜在应用程序中的热门话题。当前实现匿名的主要策略是使用伪数据包作为覆盖流量的数据包填充。但是,这种方法会带来额外的带宽成本和额外的延迟。因此,这对于匿名Web浏览应用程序是不切实际的。为了解决此问题,我们建议使用用户将要访问的预测网页作为掩盖流量,而不是虚拟数据包。此外,我们将匿名级别定义为度量匿名度的度量,并建立了一个匿名系统数学模型,并将匿名通信问题转化为优化问题。结果,用户可以在匿名级别和成本之间找到权衡。使用提出的模型,我们可以以理论风格描述和比较我们的提议和先前的模式。在真实数据集上进行的初步实验表明,该策略在节省资源方面具有巨大的潜力。

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