| 一种基于ART-2改进后的网格入侵检测模型 |
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| 引用本文： | 石红艳,戴勃,刘畅,黄绪勇. 一种基于ART-2改进后的网格入侵检测模型[J]. 辽宁工学院学报, 2010, 0(1): 11-15 |
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| 作者姓名： | 石红艳 戴勃 刘畅 黄绪勇 |
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| 作者单位： | 辽宁工业大学电子与信息工程学院;东北大学信息科学与工程学院; |
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| 基金项目： | 辽宁省教育厅科研项目(2008308) |
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| 摘 要： | 应用神经网络中的ART-2理论（adaptive resonance theory自适应共振理论），在传统ART-2模型的基础上增加了伴随神经元和重置系统B，解决入侵检测系统中可能出现的对渐变过程不敏感从而导致的预分类不完全的问题，通过与基于传统ART-2的入侵检测模型及基于朴素贝叶斯的入侵检测模型的对比，发现改进后的ART-2神经网络打破了传统ART-2对渐变过程不敏感的局限性，使得新模型能够分辨渐变过程，提高了预分类的能力。
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| 关 键 词： | 网格安全 入侵检测 ART-2 神经网络 |
Improved ART-2-based Grid Intrusion Detection Model |
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| SHI Hong-yan,DAI Bo,,LIU Chang,HUANG Xu-yong. Improved ART-2-based Grid Intrusion Detection Model[J]. Journal of Liaoning Institute of Technology(Natural Science Edition), 2010, 0(1): 11-15 |
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| Authors: | SHI Hong-yan DAI Bo LIU Chang HUANG Xu-yong |
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| Affiliation: | 1.Electron & Information Engineering College/a>;Liaoning University of Technology/a>;Jinzhou 121001/a>;China/a>;2.College of Information Science & Engineering/a>;Northeastern University/a>;Shenyang 110004/a>;China |
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| Abstract: | The neural network ART-2 theory(adaptive resonance theory) was applied,based on the traditional ART-2,the adjoint neuron and reset system B were increased to have solved the problem of the incomplete pre-classification caused by the insensitivity to the process of gradual change in the intrusion detection system.By comparison with the intrusion detection model based on the traditional ART-2 and the intrusion detection model based on Naive Bayes,the results expatiated the improved ART-2 neural network broke ... |
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| Keywords: | grid security intrusion detection system adaptive resonance theory（ART-2） neural networks |
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