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Using adaptive lossless compression to characterize network traffic

机译:使用自适应无损压缩来表征网络流量

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Detecting anomalies in network traffic is a challenging task, not only because of the inherent difficulty of identifying anomalies such as intrusions but also because of the sheer volume of data. In this paper, we attempt to extend existing work in the field of steganalysis to the problem of detecting anomalies in network traffic. By losslessly compressing network traffic using an adaptive compression algorithm, we postulate that it is possible to characterize normal network traffic. Once typical traffic has been defined, it is possible to identify anomalous traffic as the traffic that does not compress well.
机译:检测网络流量异常是一项具有挑战性的任务,这不仅是由于识别入侵等异常现象的固有困难,而且还因为数据量巨大。在本文中,我们尝试将隐写分析领域的现有工作扩展到检测网络流量异常的问题。通过使用自适应压缩算法无损压缩网络流量,我们假设可以表征正常的网络流量。一旦定义了典型流量,就可以将异常流量识别为压缩效果不佳的流量。

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