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A Bayesian Classification Intrusion Detection Method Based on the Fusion of PCA and LDA
Joint Authors
Shen, Zhidong
Chen, Weiying
Zhang, Yuhao
Source
Security and Communication Networks
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-12-28
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Information Technology and Computer Science
Abstract EN
The rapid development of network technology is facing severe security threats while bringing convenience to people.
How to build a secure network environment has become an important guarantee for social development.
Intrusion detection plays an important role in the field of network security.
With the complexity and diversification of networks, intrusion detection systems also need to be constantly improved and developed to match external environmental changes.
The innovative work of this paper is as follows: principal component analysis and linear discriminant analysis are used to reduce the dimensionality of the data set, which avoids unnecessary detection content and improves detection efficiency and accuracy.
The principal component analysis method, linear discriminant analysis algorithm, and Bayesian classification are combined to construct the PCA-LDA-BC classification algorithm, and the intrusion detection model is established based on this algorithm.
The simulation experiment was carried out on the algorithm CICIDS2017 data set proposed in this paper.
From the experimental results, it can be analysed that in the intrusion detection of missing data, the improved algorithm is compared with the traditional naive Bayesian classification algorithm, the detection rate is improved, and the false detection rate and the missed alarm rate are reduced.
In terms of intrusion detection for various types of attacks, the detection rate, false detection rate, and missed alarm rate have been improved accordingly.
It is proved that the algorithm has certain validity and feasibility.
American Psychological Association (APA)
Shen, Zhidong& Zhang, Yuhao& Chen, Weiying. 2019. A Bayesian Classification Intrusion Detection Method Based on the Fusion of PCA and LDA. Security and Communication Networks،Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1210511
Modern Language Association (MLA)
Shen, Zhidong…[et al.]. A Bayesian Classification Intrusion Detection Method Based on the Fusion of PCA and LDA. Security and Communication Networks No. 2019 (2019), pp.1-11.
https://search.emarefa.net/detail/BIM-1210511
American Medical Association (AMA)
Shen, Zhidong& Zhang, Yuhao& Chen, Weiying. A Bayesian Classification Intrusion Detection Method Based on the Fusion of PCA and LDA. Security and Communication Networks. 2019. Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1210511
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1210511