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CNID: Research of Network Intrusion Detection Based on Convolutional Neural Network
Joint Authors
Source
Discrete Dynamics in Nature and Society
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-05-21
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Liu, Guojie& Zhang, Jianbiao. 2020. CNID: Research of Network Intrusion Detection Based on Convolutional Neural Network. Discrete Dynamics in Nature and Society،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1153082
Modern Language Association (MLA)
Liu, Guojie& Zhang, Jianbiao. CNID: Research of Network Intrusion Detection Based on Convolutional Neural Network. Discrete Dynamics in Nature and Society No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1153082
American Medical Association (AMA)
Liu, Guojie& Zhang, Jianbiao. CNID: Research of Network Intrusion Detection Based on Convolutional Neural Network. Discrete Dynamics in Nature and Society. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1153082
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1153082