| 一种基于改进的BP神经网络的入侵检测方法 |
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| 引用本文： | 王海艳,李根,王汝传. 一种基于改进的BP神经网络的入侵检测方法[J]. 南通大学学报(自然科学版), 2010, 9(3) |
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| 作者姓名： | 王海艳 李根 王汝传 |
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| 作者单位： | 南京邮电大学,计算机学院,江苏,南京,210003 |
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| 基金项目： | 江苏省自然科学基金项目 |
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| 摘 要： | 针对普通BP神经网络算法学习收敛速度慢、易造成局部极小的问题,提出一种改进的BP神经网络入侵检测方法,其采用拟牛顿的方法进行学习,即对目标矩阵求二阶导数.运用该方法能够有效提高学习速度,消除局部极小.仿真结果表明,改进的BP神经网络入侵检测方法收敛速度快,比标准的BP入侵检测方法误检率低,能够很好地提高学习效率,更加有效地检测攻击行为.
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| 关 键 词： | BP神经网络 入侵检测 收敛速度 |
Intrusion Detection Method Based on Improved BP Neural Network |
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| WANG Hai-yan,LI Gen,WANG Ru-chuan. Intrusion Detection Method Based on Improved BP Neural Network[J]. Journal of Nantong University (Natural Science Edition), 2010, 9(3) |
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| Authors: | WANG Hai-yan LI Gen WANG Ru-chuan |
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| Affiliation: | WANG Hai-yan,LI Gen,WANG Ru-chuan(School of Computer Science and Technology,Nanjing University of Posts and Telecommunications,Nanjing 210003,China) |
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| Abstract: | General BP neural network algorithm has a low constringency speed,which will easily result in a local minimization problem.An advanced intrusion detection method based on improved BP neural network is proposed.It adopts the Newtonian method to seek the second rank differential coefficient of the target matrix and can expedite learning speed rapidly and clear up part particle.Simulation results demonstrate that the intrusion detection method based on improved BP neural network,with a higher constringency spe... |
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| Keywords: | BP neural network intrusion detection constringency speed |
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