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Predicted Packet Padding for Anonymous Web Browsing Against Traffic Analysis Attacks

机译:针对流量分析攻击的匿名Web浏览的预测数据包填充

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摘要

Anonymous communication has become a hot research topic in order to meet the increasing demand for web privacy protection. However, there are few such systems which can provide high level anonymity for web browsing. The reason is the current dominant dummy packet padding method for anonymization against traffic analysis attacks. This method inherits huge delay and bandwidth waste, which inhibits its use for web browsing. In this paper, we propose a predicted packet padding strategy to replace the dummy packet padding method for anonymous web browsing systems. The proposed strategy mitigates delay and bandwidth waste significantly on average. We formulated the traffic analysis attack and defense problem, and defined a metric, cost coefficient of anonymization (CCA), to measure the performance of anonymization. We thoroughly analyzed the problem with the characteristics of web browsing and concluded that the proposed strategy is better than the current dummy packet padding strategy in theory. We have conducted extensive experiments on two real world data sets, and the results confirmed the advantage of the proposed method.
机译:为了满足对网络隐私保护日益增长的需求,匿名通信已成为研究的热点。但是,很少有可以为Web浏览提供高级匿名性的系统。原因是当前用于对流量分析攻击进行匿名处理的主要伪数据包填充方法。此方法继承了巨大的延迟和带宽浪费,从而限制了其在Web浏览中的使用。在本文中,我们提出了一种预测的数据包填充策略来代替匿名Web浏览系统中的虚拟数据包填充方法。所提出的策略平均可显着减少延迟和带宽浪费。我们制定了流量分析攻防问题,并定义了一个度量标准,即匿名化成本系数(CCA),以衡量匿名化的性能。通过对网页浏览特性的深入分析,得出理论上该策略优于目前的虚拟包填充策略。我们在两个真实世界的数据集上进行了广泛的实验,结果证实了该方法的优势。

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