Dynamic Evolution Systems and Applications in Intrusion Detection Systems

Xian-Ming Xu, J. Zhan
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引用次数: 1

Abstract

In this paper, we present a dynamic evolution system and build up a model to trace the transition of the system state. This new model differs from the previous methods, such as Bayesian network, artificial neural network, in two aspects: it can adapt the changes of the environment automatically, and it does not need a special training phase to build up a model. Theoretical analysis shows that it is applicable and practical, and furthermore, experimental results show that it has good performance especially in dynamic environment.
动态演化系统及其在入侵检测系统中的应用
本文提出了一个动态演化系统,并建立了一个跟踪系统状态转变的模型。这种新模型与以往的贝叶斯网络、人工神经网络等方法的不同之处在于:它可以自动适应环境的变化,不需要专门的训练阶段来建立模型。理论分析表明了该方法的适用性和实用性,实验结果表明该方法在动态环境下具有良好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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