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Using Wavelets for Compression and Detecting Events in Anomalous Network Traffic

机译:使用小波压缩和检测异常网络流量中的事件

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Monitoring and measuring various metrics of high-data rate networks produces a vast amount of information over a long period of time making the storage of the monitored data a serious issue. Furthermore, for the collected monitoring data to be useful to network analysts, these measurements need to be processed in order to detect interesting characteristics.In this paper wavelet analysis is used as a multi-resolution analysis tool for compression of data rate measurements. Two known thresholds are suggested for lossy compression and event detection purposes. Results show high compression ratios while preserving the quality (quantitative and visual aspects) and the energy of the signal and detection of sudden changes are achievable.
机译:监视和测量高数据速率网络的各种指标会在很长一段时间内产生大量信息,从而使监视数据的存储成为一个严重的问题。此外,为了使收集到的监视数据对网络分析人员有用,需要对这些测量进行处理以检测有趣的特征。在本文中,小波分析被用作压缩数据速率测量的多分辨率分析工具。建议两个已知阈值用于有损压缩和事件检测目的。结果表明,在保持质量(定量和视觉方面)的同时,压缩率很高,并且可以实现信号的能量和突然变化的检测。

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