scholarly journals Network Intrusion Detection Model With Clustering Ensemble Method

2015 ◽  
Vol 9 (11) ◽  
pp. 239-250
Author(s):  
Liang-Wei Chen
2020 ◽  
Author(s):  
Xiao Zheng ◽  
Yu Wang ◽  
Luliang Jia ◽  
Dapeng Xiong ◽  
Jie Qiang

2013 ◽  
Vol 765-767 ◽  
pp. 1415-1418 ◽  
Author(s):  
Ya Fang Lou ◽  
Zhi Jun Yuan ◽  
Hao Wu

As the network is impacting enormously to all aspects of society, the network security becomes a critical problem. The traditional intrusion detection technology exists some disadvantages: the imperfection of architecture, the slow detecting of system, the vulnerable of itself architecture, and so on. This paper presents an intrusion detection model based on BP neural network which has the incomparable advantages against traditional intrusion detection systems. Therefore, the study of this subject possesses the practical significance.


2020 ◽  
Vol 1617 ◽  
pp. 012082
Author(s):  
Qingchuan Meng ◽  
Youzi Zhang ◽  
Fengzhi Wu ◽  
Xiaoming Chen

Author(s):  
Ahmed Shafee ◽  
Mohamed Baza ◽  
Douglas A. Talbert ◽  
Mostafa M. Fouda ◽  
Mahmoud Nabil ◽  
...  

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