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Network intrusion detection based on IPSO-BPNN

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成果类型:
期刊论文
作者:
Zhao, Yuhong;Zhao, Yirui;Zhao, Xuecheng
通讯作者:
Zhao, Y.
作者机构:
[Zhao, Yirui; Zhao, Yuhong] School of Electric Engineering, University of South China, Hengyang, 421001, Hunan, China
[Zhao, Xuecheng] Mechanical and Electrical Engineering Department, Shaoyang Vocational and Technical, Shaoyang, Hunan, China
通讯机构:
[Zhao, Y.] S
School of Electric Engineering, University of South China, China
语种:
英文
关键词:
Network intrusion detection;Neural network;Particle swarm optimization
期刊:
Information Technology Journal
ISSN:
1812-5638
年:
2013
卷:
12
期:
14
页码:
2719-2725
机构署名:
本校为第一且通讯机构
院系归属:
电气工程学院
摘要:
In order to resolve the problem of high false positive rate of traditional intrusion detection algorithm, the hybrid algorithm which combines Improved Particle Swarm Optimization (IPSO) with Back Propagation (BP) neural network algorithm is used in computer network intrusion detection in this study. Based on the characteristics of the local precise search of the BP networks and the global search of the improved particle swarm optimization algorithm, this method optimizes the weight of the BP networks, conquers the disadvantages of the BP networ...

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