Network Intrusion Detection Model Based on Improved Convolutional Neural Network

2020 ◽  
pp. 18-24
Author(s):  
Sile Li
Keyword(s):  
Neural Network ◽  
Intrusion Detection ◽  
Convolutional Neural Network ◽  
Network Intrusion Detection ◽  
Detection Model ◽  
Model Based ◽  
Network Intrusion

scholarly journals CNID: Research of Network Intrusion Detection Based on Convolutional Neural Network

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Guojie Liu ◽  
Jianbiao Zhang
Keyword(s):  
Neural Network ◽  
Intrusion Detection ◽  
Convolutional Neural Network ◽  
Detection System ◽  
False Positive Rate ◽  
Network Intrusion Detection ◽  
Test Results ◽  
Softmax Classifier ◽  
Detection Model ◽  
Network Intrusion

Network intrusion detection system can effectively detect network attack behaviour, which is very important to network security. In this paper, a multiclassification network intrusion detection model based on convolutional neural network is proposed, and the algorithm is optimized. First, the data is preprocessed, the original one-dimensional network intrusion data is converted into two-dimensional data, and then the effective features are learned using optimized convolutional neural networks, and, finally, the final test results are produced in conjunction with the Softmax classifier. In this paper, KDD-CUP 99 and NSL-KDD standard network intrusion detection dataset were used to carry out the multiclassification network intrusion detection experiment; the experimental results show that the multiclassification network intrusion detection model proposed in this paper improves the accuracy and check rate, reduces the false positive rate, and also obtains better test results for the detection of unknown attacks.

Network Intrusion Detection Model based on Chi-square Test and Stacking Approach

2020 ◽  
Author(s):  
Xiao Zheng ◽  
Yu Wang ◽  
Luliang Jia ◽  
Dapeng Xiong ◽  
Jie Qiang
Keyword(s):  
Intrusion Detection ◽  
Network Intrusion Detection ◽  
Chi Square ◽  
Detection Model ◽  
Model Based ◽  
Network Intrusion ◽  
Chi Square Test

The Application of BP Neural Network in Network Intrusion Detection

2013 ◽  
Vol 765-767 ◽  
pp. 1415-1418 ◽  
Author(s):  
Ya Fang Lou ◽  
Zhi Jun Yuan ◽  
Hao Wu
Keyword(s):  
Neural Network ◽  
Intrusion Detection ◽  
Bp Neural Network ◽  
Practical Significance ◽  
Network Intrusion Detection ◽  
Critical Problem ◽  
Detection Model ◽  
Detection Systems ◽  
Network Intrusion ◽  
Detection Technology

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.

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