| 基于学习Petri网的网络入侵检测方法 |
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| 引用本文： | 危胜军,胡昌振,高秀峰.基于学习Petri网的网络入侵检测方法[J].兵工学报,2006,27(2):269-272. |
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| 作者姓名： | 危胜军 胡昌振 高秀峰 |
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| 作者单位： | 北京理工大学,网络安全技术实验室,北京,100081;北京理工大学,网络安全技术实验室,北京,100081;北京理工大学,网络安全技术实验室,北京,100081 |
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| 摘 要： | 基于神经网络的入侵检测方法存在学习速度慢，不易收敛，分类能力不足等缺点。采用 学习Petri网（LPN)建立了对网络入侵的检测分类方法，该方法在非线性和不连续函数的实现上优 于神经网络，实验结果表明：基于LPN的入侵分类相对于相同结构的神经网络具有更高的识别精 度以及更快的学习速率。
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| 关 键 词： | 计算机系统结构 入侵检测 学习Petri网 神经网络 |
| 文章编号： | 1000-1093（2006）02-0269-04 |
| 收稿时间： | 2005-03-18 |
| 修稿时间： | 2005-03-18 |
A Detection Method of Network Intrusion Based on Learning Petri Nets |
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| WEI Sheng-jun,HU Chang-zhen,GAO Xiu-feng.A Detection Method of Network Intrusion Based on Learning Petri Nets[J].Acta Armamentarii,2006,27(2):269-272. |
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| Authors: | WEI Sheng-jun HU Chang-zhen GAO Xiu-feng |
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| Affiliation: | Network Security Technique Laboratory, Beijing Institute of Technology, Beijing 100081，China |
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| Abstract: | A method of intrusion detection based on neural network(NN) has flaws of slower learning speed,hardness in converging and deficiency of classifier capability.The learning Petri nets(LPN) were adopted to construct the method of network intrusion detection.LPN is superior to NN in the realization of nonlinear and discontinuous functions.The test result indicates that the classifier based on LPN has better recognizing precision and faster learning speed compared with the classifier based on the same structure NN. |
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| Keywords: | computer system architecture intrusion detection learning Petri nets neural network |
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