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Research and Simulation of Network Intrusion Detection Algorithm Based on Fuzzy Classification

机译:基于模糊分类的网络入侵检测算法研究与仿真

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摘要

The network intrusion accurate detection problem is researched. In the network intrusion detection process, the classification features of network operation data has poor uniformity, and the error of features classification is large, a network intrusion detection method based on fuzzy classification algorithm is proposed, principal component analysis method is used, the dimensions of network operation data are reduced. The redundant data are reduced, and fuzzy classification method is used, network intrusion featuresare classified, the network intrusion detection is realized. The simulation results show that the algorithm can effectively improve the accuracy of detection, it has perfect results.
机译:研究了网络入侵准确的检测问题。在网络入侵检测过程中,网络操作数据的分类特征具有差的均匀性差,特征分类的误差大,提出了一种基于模糊分类算法的网络入侵检测方法,使用了主要成分分析方法,尺寸网络操作数据减少。冗余数据减少,使用模糊分类方法,网络入侵功能分类,实现网络入侵检测。仿真结果表明,该算法可以有效提高检测的准确性,它具有完美的结果。

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