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Intrusion detection based on fuzzy reasoning

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成果类型:
期刊论文、会议论文
作者:
Yu Fei*;Shen Yue;Liao Guiping;Zhang Linfeng;Xu Cheng
通讯作者:
Yu Fei
作者机构:
[Zhang Linfeng; Liao Guiping; Shen Yue; Yu Fei] Hunan Agr Univ, Sch Comp & Informat Engn, Changsha 410128, Hunan, Peoples R China.
[Yu Fei; Xu Cheng] Guangdong Univ Business Studies, Guangdong Prov Key Lab Elect Commerce Market Appl, Guangzhou 510320, Guangdong, Peoples R China.
[Xu Cheng] Suzhou Univ, Jiangsu Prov Key Lab Comp Informat Proc Technol, Suzhou 2150063, Peoples R China.
通讯机构:
[Yu Fei] H
Hunan Agr Univ, Sch Comp & Informat Engn, Changsha 410128, Hunan, Peoples R China.
语种:
中文
关键词:
fuzzy neural network;fuzzy reasoning;intrusion detection;network processor
期刊:
Proceedings of the 26th Chinese Control Conference, CCC 2007
年:
2007
页码:
331-335
会议名称:
26th Chinese Control Conference, CCC 2007
会议时间:
July 26, 2007 - July 31, 2007
会议地点:
Zhangjiajie, China
机构署名:
本校为第一且通讯机构
院系归属:
信息科学技术学院
摘要:
The paper proposes a new network intrusion detection system based on fuzzy neural network by redesigning the intrusion detection system's architecture and arithmetic. In order to overcome the difficulty of specifying the membership function of rules depending on experiences of experts in multi-dimension space.,neural network is introduced to distinguish non-linearly input/output characteristics of complex system and to generate rule sets and membership functions automatically. The new architecture adopts the network processor to collect and analyse the data in the low layer of network.,and to ...

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