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| 决策树与神经网络结合的入侵检测系统模型研究 | |
| 引用本文： | 王妍妍,王艳宁,王敏.决策树与神经网络结合的入侵检测系统模型研究[J].燕山大学学报,2010,34(1):85-89. |
| 作者姓名： | 王妍妍 王艳宁 王敏 |
| 作者单位： | 1. 燕山大学,图书馆,河北,秦皇岛,066004 2. 燕山大学,理学院,河北,秦皇岛,066004 3. 燕山大学,研究生学院,河北,秦皇岛,066004 |
| 基金项目： | 河北省科技支撑计划资助项目(072135218) |
| 摘 要： | 入侵检测系统是保证网络信息安全的有力手段,文中提出一种结合决策树和神经网络的入侵检测系统框架。决策树分类方法把数据集划分为正常数据和入侵数据,并作为训练集分别用神经网络进行训练,改善了系统的检测精度并提高了对未知数据的检测能力。离线训练后的系统可以实现网络数据的实时检测,通过实验证明了此系统很好的检测效果和自适应能力。 |
| 关 键 词： | 入侵检测 决策树 神经网络 |
Intrusion detection system model based on decision tree and neural network |
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| WANG Yan-yan,WANG Yan-ning,WANG Min.Intrusion detection system model based on decision tree and neural network[J].Journal of Yanshan University,2010,34(1):85-89. | |
| Authors: | WANG Yan-yan WANG Yan-ning WANG Min |
| Institution: | 1.Library;Yanshan University;Qinhuangdao;Hebei 066004;China;2.College of Sciences;3.Graduate Department;China |
| Abstract: | Intrusion detection system is an efficient method for information security.An intrusion detection system framework based on decision tree and neural network is proposed in this paper.Dataset can be labeled normal or intrusion based on decision tree,which are transferred to neural network as training dataset.After training of the neural network,IDS improved its accuracy and ability to detect new intrusion.IDS can detect intrusion online efficiently and adaptively in our experiment. |
| Keywords: | intrusion detection decision tree neural network |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |