| 遗传算法优化模糊神经网络的入侵检测模型 |
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| 引用本文： | 程丽丽,孙名松.遗传算法优化模糊神经网络的入侵检测模型[J].哈尔滨理工大学学报,2005,10(2):8-11. |
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| 作者姓名： | 程丽丽 孙名松 |
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| 作者单位： | 哈尔滨理工大学,计算机与控制学院,黑龙江,哈尔滨,150080;哈尔滨理工大学,计算机与控制学院,黑龙江,哈尔滨,150080 |
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| 基金项目： | 黑龙江省自然科学基金项目(F0306) |
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| 摘 要： | 针对目前大多数的入侵检测系统存在的局限性，依据通用入侵检测框架CIDF，提出了一种利用遗传算法优化网络参数的基于模糊神经网络的入侵检测模型，分析了入侵模糊特征、模糊神经网络的学习优化问题，给出了此模型中模糊神经网络模块的训练算法．仿真实验结果表明，该检测算法可以有效地进行入侵检测，检测效率达到95％以上．
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| 关 键 词： | 入侵检测 模糊神经网络 遗传算法 |
| 文章编号： | 1007-2683(2005)02-0008-04 |
| 修稿时间： | 2004年11月10 |
Intrusion Detection Model Based on Fuzzy Neural Network Optimized by Genetic Algorithm |
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| CHENG Li-li,SUN Ming-song.Intrusion Detection Model Based on Fuzzy Neural Network Optimized by Genetic Algorithm[J].Journal of Harbin University of Science and Technology,2005,10(2):8-11. |
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| Authors: | CHENG Li-li SUN Ming-song |
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| Abstract: | Aimed at the limitation of most intrusion detection systems, according to the common intrusion detection frame CIDF, in this article a fuzzy neural network for intrusion detection model optimized by genetic algorithm is proposed, moreover we analyze the features of fuzzy intrusion and the optimization of the fuzzy neural network, establishing an algorithm for fuzzy neural network model. The emulational experiments prove that the algorithm can detect intrusion effectively, and the intrusion detection rate is above 95 percent. |
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| Keywords: | intrusion detection fuzzy neural network genetic algorithm |
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