A New Sketch Method for Measuring Host Connection Degree Distribution

A New Sketch Method for Measuring Host Connection Degree Distribution
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测量主机连接度分布的新草图方法

DOI:
10.1109/tifs.2014.2312544
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发表时间:
2014-06
影响因子:
6.8
通讯作者:
Qin Tao
Qin Tao
中科院分区:
计算机科学1区
文献类型:
--
作者:
Wang Pinghui;Guan Xiaohong;Zhao Junzhou;Tao Jing;Qin Tao

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主机连接度分布(HCDD)是网络安全监测的重要指标。然而,对于具有大量业务数据的高速链路,难以在真实的时间中准确地获得HCDD。在本文中,我们提出了一种新的草图方法来建立一个主机的流量使用一个统一的Flajolet-Martin草图结合一个小位图的概率流量摘要。为了研究它的性能与以前的采样和草图方法相比,我们提出了一个通用的模型,包括所有这些方法。使用该模型,我们计算了Cramér-Rao下界和HCCD估计的方差。理论分析和数值实验结果表明,我们的草图方法是六倍以上的精度比国家的最先进的方法,具有相同的内存使用。
The host connection degree distribution (HCDD) is an important metric for network security monitoring. However, it is difficult to accurately obtain the HCDD in real time for high-speed links with a massive amount of traffic data. In this paper, we propose a new sketch method to build a probabilistic traffic summary of a host's flows using a uniform Flajolet-Martin sketch combined with a small bitmap. To study its performance in comparison with previous sampling and sketch methods, we present a general model that encompasses all these methods. With this model, we compute the Cramér-Rao lower bounds and the variances of HCDD estimations. The theoretic analysis and numerical experimental results show that our sketch method is six times more accurate than state-of-the-art methods with the same memory usage.
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