[1]张军.网络入侵环境下健康节点选择方法设计与仿真[J].华侨大学学报(自然科学版),2016,37(6):754-757.[doi:10.11830/ISSN.1000-5013.201606018]
　ZHANG Jun.Health Design and Simulation of the Node Selection Method in Environment of Network Intrusion[J].Journal of Huaqiao University(Natural Science),2016,37(6):754-757.[doi:10.11830/ISSN.1000-5013.201606018]
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网络入侵环境下健康节点选择方法设计与仿真()
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《华侨大学学报（自然科学版）》[ISSN:1000-5013/CN:35-1079/N]

卷:
第37卷
期数:
2016年第6期
页码:
754-757
栏目:
出版日期:
2016-11-20

文章信息/Info

Title:
Health Design and Simulation of the Node Selection Method in Environment of Network Intrusion
文章编号:
1000-5013(2016)06-0754-04
作者:
张军
江苏海事职业技术学院 信息工程系, 江苏 南京 211170
Author(s):
ZHANG Jun
Department of Information and Engineering, Jiangsu Maritime Institute, Nanjing 211170, China
关键词:
网络入侵;  健康节点;  模糊约束;  BP神经网络;  粒子群算法
Keywords:
network invasion;  health node;  fuzzy constraints;  BP neural networks;  particle swarm algorithm
分类号:
TP127
DOI:
10.11830/ISSN.1000-5013.201606018
文献标志码:
A
摘要:
提出一种网络入侵环境下健康节点通信选择算法.针对节点特征建立模糊数学模型,对健康节点选择的成本进行约束,引入粒子群优化算法,结合不确定因素,对参数进行优化,实现健康节点的选择.实验结果表明:与传统的BP神经网络方法相比,改进的网络入侵环境下健康节点通信选择算法提高了健康节点选择的精度,缩短了运行时间,能将入侵后的误差控制在合理的范围内.
Abstract:
Accurately selectting health node in network intrusion environment can guarantee the normal operation of the network. Fuzzy mathematics model is established based on the node characteristics to constraint the cost of the health node selection. Introducing the particle swarm optimization algorithm combining with the uncertainties to optimize the parameters, and to achieve healthy node selection. The experimental results show that compared with the traditional BP neural network method, the improved network intrusion environment health communication node selection algorithm improved the precision of node selection of health, shorten the operation time. After the invasion, the error can be controlled in a reasonable range.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2016-10-13
通信作者: 张军(1973-),男,副教授,主要从事网络安全技术、量子通信理论的研究.E-mail:njhxzhr@163.com.
基金项目: 江苏省现代教育技术重点研究课题(2015-R-42639)
更新日期/Last Update: 2016-11-20