| 基于进化神经网络的入侵检测模型 |
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| 引用本文： | 杨鸿洲 杨立洁. 基于进化神经网络的入侵检测模型[J]. 刑警与科技, 2005, 25(3): 62-65 |
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| 作者姓名： | 杨鸿洲 杨立洁 |
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| 作者单位： | [1]山东大学信息科学与工程学院,山东济南250100 [2]济南大学控制科学与工程学院,山东济南250022 |
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| 摘 要： | 当前的入侵检测技术主要有基于规则的误用检测和基于统计的异常检测。本文提出一个基于遗传算法的神经网络入侵检测系统模型，该模型将神经网络与遗传算法结合起来，利用神经网络自学习、自适应的特性，同时克服了神经网络易陷入局部最优，训练速度慢的缺点。该模型具有智能特性，能够较好地识别新的攻击。
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| 关 键 词： | 网络安全 神经网络 入侵检测 遗传算法 |
| 文章编号： | 1672-2396[2005]12-08-09 |
| 收稿时间： | 2005-09-06 |
| 修稿时间： | 2005-09-06 |
Intrusion Detection Model Based on Evolutionary Neural Network |
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| Yang Hongzhou, Yang Lijie. Intrusion Detection Model Based on Evolutionary Neural Network[J]. Criminal Police & Technology, 2005, 25(3): 62-65 |
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| Authors: | Yang Hongzhou Yang Lijie |
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| Affiliation: | 1School of Information Science and Engineering, Shandong University, Jinan 250100 China;2School of Control Science and Engineering, Jinan University, Jinan 250022 China |
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| Abstract: | The current intrusion detection techniques mainly include rule-based misuse detection and statistics-based anomaly detection. This paper proposed an intrusion detection model based on evolutionary artificial neural network.The model combines the neural network with genetic algorithm. Not only can its capabilities of learning. quick classification and processing of noisy data be used in intrusion detection, the system can also get over the insufficiency of BP algorithm,such as:liable to get into local minimum,slow speed in trainging. |
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| Keywords: | Network security Neural network Intrusion detection Genetic algorithm |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
