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THE APPLICATION OF ROUGH SETS ON NETWORK INTRUSION DETECTION

机译:粗糙集在网络入侵检测中的应用

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摘要

With a growing amount of network information flowing, the limitations of the traditional network IDSs become more and more obvious, which can not adapt to the increasing trend of novel network attacks and data quantities.As a result, the analysis process becomes time-consuming.Fortunately, as is well known, Rough Set's reduction theory can effectively avoid redundancy and reduce extra attributes.Therefore, to solve the problems in IDSs, the paper advocates using the theory of rough set to improve the attribute reduction algorithm.Experimental results show that the number of attributes can be reduced 64% using the proposed method.Thus, it can be concluded that the presented method can shorten detection process efficiently.
机译:随着网络信息流的增加,传统网络IDS的局限性越来越明显,无法适应新型网络攻击和数据量的增长趋势,因此分析过程变得很耗时。幸运的是,众所周知,粗糙集的约简理论可以有效避免冗余并减少多余的属性,因此,为解决IDS中的问题,本文提倡使用粗糙集的理论来改进属性约简算法。使用该方法可以将属性数量减少64%。因此可以得出结论,该方法可以有效地缩短检测过程。

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