Compromising anonymous communication systems using blind source separation
Compromising anonymous communication systems using blind source separation
复制标题
DOI：
10.1145/1609956.1609964
复制
发表时间：
2009-10
期刊：
影响因子：
--
通讯作者：
Ye Zhu;R. Bettati
中科院分区：
文献类型：
--
作者：
Ye Zhu;R. Bettati
针对有线和无线匿名网络提出了一类匿名攻击。这些攻击基于盲源分离算法，该算法广泛用于从统计信号处理中的信号混合物中恢复单个信号。由于当前匿名网络设计背后的理念是混合流量或隐藏在人群中，因此提出的匿名攻击非常有效。针对有线匿名网络提出的流分离攻击可以分离混合网络中的流量。实验结果表明，该攻击是有效的、可扩展的。通过将流分离方法与频谱匹配相结合，被动攻击者可以获得混合网络的流量图。我们使用一个非平凡的网络来证明组合攻击是有效的。针对无线网络的匿名攻击可以使用非常简单的传感器集合来识别完全匿名的无线网络中的节点。基于由传感器提供的匿名数据包的计数的时间序列，我们估计的节点数量与使用主成分分析。然后，我们继续将收集到的数据包数据分成流量，在可用传感器的空间多样性的帮助下，可以用来估计无线节点的位置。我们的模拟实验表明，估计器表现出高精度和高置信度的匿名TCP流量。额外的实验表明，估计器在匿名无线网络中使用流量填充执行得非常好。
We propose a class of anonymity attacks to both wired and wireless anonymity networks. These attacks are based on the blind source separation algorithms widely used to recover individual signals from mixtures of signals in statistical signal processing. Since the philosophy behind the design of current anonymity networks is to mix traffic or to hide in crowds, the proposed anonymity attacks are very effective. The flow separation attack proposed for wired anonymity networks can separate the traffic in a mix network. Our experiments show that this attack is effective and scalable. By combining the flow separation method with frequency spectrum matching, a passive attacker can derive the traffic map of the mix network. We use a nontrivial network to show that the combined attack works. The proposed anonymity attacks for wireless networks can identify nodes in fully anonymized wireless networks using collections of very simple sensors. Based on a time series of counts of anonymous packets provided by the sensors, we estimate the number of nodes with the use of principal component analysis. We then proceed to separate the collected packet data into traffic flows that, with help of the spatial diversity in the available sensors, can be used to estimate the location of the wireless nodes. Our simulation experiments indicate that the estimators show high accuracy and high confidence for anonymized TCP traffic. Additional experiments indicate that the estimators perform very well in anonymous wireless networks that use traffic padding.