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基于神经网络集成的入侵检测研究
Intrusion detection based on neural network ensemble
【摘要】 提出一种新的基于神经网络集成的入侵检测方法。首先通过有区别地对待不同的训练数据训练神经网络,提高对小类别入侵的检测能力并防止网络训练中的退化现象;然后利用一种新的改进遗传算法优化集成网络的权,提高系统整体性能。理论和实验表明该方法具有较好的检测能力。
【Abstract】 This paper put forward a new intrusion detection method based on neural network ensemble. First, we trained neural network by using different methods to deal with different data, to elevate the ability of detecting small intrusion and prevent neural network degeneration during training; then, the improved Genetic Algorithm was used to optimize neural network ensemble weight. Theory and experiment show that this method has better ability in intrusion detection.
【关键词】 入侵检测;
遗传算法;
神经网络集成;
【Key words】 intrusion detection; generation algorithm; neural network ensemble;
【Key words】 intrusion detection; generation algorithm; neural network ensemble;
【基金】 国家自然科学基金资助项目(60373062,60573045)
- 【文献出处】 计算机应用 ,Journal of Computer Applications , 编辑部邮箱 ,2007年06期
- 【分类号】TP393.08
- 【被引频次】8
- 【下载频次】206