| 一种基于改进神经网络的入侵容忍系统模型 |
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| 引用本文： | 秦华旺,戴跃伟,王执铨.一种基于改进神经网络的入侵容忍系统模型[J].南京理工大学学报(自然科学版),2008,32(5). |
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| 作者姓名： | 秦华旺 戴跃伟 王执铨 |
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| 作者单位： | 南京理工大学,自动化学院,江苏,南京,210094 |
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| 基金项目： | 国家自然科学基金(60374066) |
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| 摘 要： | 该文通过对资源和控制两个属性的分析，将入侵容忍系统的运行状态进行了抽象分类，给出了系统不同运行状态下的相应安全机制；利用改进的反向传播（BP）神经网络对入侵容忍系统建模，给出了BP网络的输入和输出节点以及基于该BP网络的系统工作原理，用实例描述了该系统的一个典型的入侵容忍过程；实验结果表明，该系统对入侵具有较好的检测和容忍能力。
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| 关 键 词： | 入侵容忍 神经网络 反向传播网络 |
Model of Intrusion Tolerant System Based on Improved Neural Networks |
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| QIN Hua-wang,DAI Yue-wei,WANG Zhi-quan.Model of Intrusion Tolerant System Based on Improved Neural Networks[J].Journal of Nanjing University of Science and Technology(Nature Science),2008,32(5). |
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| Authors: | QIN Hua-wang DAI Yue-wei WANG Zhi-quan |
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| Institution: | School of Automation;NUST;Nanjing 210094;China |
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| Abstract: | The work states of intrusion tolerant system are classified abstractly through analyzing the two attributes: resource and control.The corresponding safe mechanisms in different work states of the system are given.A model of intrusion tolerant system based on improved back propagation(BP) neural networks is established,the input and output nodes of the BP network are given,and the work principle of the system based on the BP network is described.A typical intrusion tolerant process of the system is described... |
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| Keywords: | intrusion tolerance neural networks back propagation network |
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