Exposing invisible timing-based traffic watermarks with BACKLIT

Xiapu Luo, Peng Zhou, Junjie Zhang, R. Perdisci, Wenke Lee, R. Chang
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引用次数: 37

Abstract

Traffic watermarking is an important element in many network security and privacy applications, such as tracing botnet C&C communications and deanonymizing peer-to-peer VoIP calls. The state-of-the-art traffic watermarking schemes are usually based on packet timing information and they are notoriously difficult to detect. In this paper, we show for the first time that even the most sophisticated timing-based watermarking schemes (e.g., RAINBOW and SWIRL) are not invisible by proposing a new detection system called BACKLIT. BACKLIT is designed according to the observation that any practical timing-based traffic watermark will cause noticeable alterations in the intrinsic timing features typical of TCP flows. We propose five metrics that are sufficient for detecting four state-of-the-art traffic watermarks for bulk transfer and interactive traffic. BACKLIT can be easily deployed in stepping stones and anonymity networks (e.g., Tor), because it does not rely on strong assumptions and can be realized in an active or passive mode. We have conducted extensive experiments to evaluate BACKLIT's detection performance using the PlanetLab platform. The results show that BACKLIT can detect watermarked network flows with high accuracy and few false positives.
暴露不可见的时间为基础的交通水印与背光
流量水印是许多网络安全和隐私应用中的重要元素,例如跟踪僵尸网络C&C通信和去匿名点对点VoIP呼叫。最先进的流量水印方案通常是基于数据包时间信息的,并且它们非常难以检测。在本文中,我们首次展示了即使是最复杂的基于时间的水印方案(例如,RAINBOW和SWIRL)也不是不可见的,并提出了一种称为BACKLIT的新检测系统。BACKLIT是根据观察设计的,任何实际的基于时间的流量水印都会引起TCP流固有时间特征的明显改变。我们提出了五个指标,足以检测四个最先进的流量水印,用于批量传输和交互流量。BACKLIT可以很容易地部署在垫脚石和匿名网络(例如Tor)中,因为它不依赖于强假设,可以在主动或被动模式下实现。我们已经使用PlanetLab平台进行了大量的实验来评估BACKLIT的检测性能。实验结果表明,BACKLIT算法对带水印的网络流检测精度高,误报率低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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