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A New Intrusion Detection Algorithm AE-3WD for Industrial Control Network

Yongzhong Li1,2,*, Cong Li1, Yuheng Li3, Shipeng Zhang2

1 School of Computer Science and Engineering, Taizhou Institute of Sci. and Tec. NJUST, Taizhou, 225300, China
2 School of Computer Science, Jiangsu University of Science and Technology, Zhenjiang, 212003, China
3 Suzhou Institute of Technology, Jiangsu University of Science and Technology, Suzhou, 215600, China

* Corresponding Author: Yongzhong Li. Email: email

Journal of New Media 2022, 4(4), 205-217. https://doi.org/10.32604/jnm.2022.034778

Abstract

In this paper, we propose a intrusion detection algorithm based on auto-encoder and three-way decisions (AE-3WD) for industrial control networks, aiming at the security problem of industrial control network. The ideology of deep learning is similar to the idea of intrusion detection. Deep learning is a kind of intelligent algorithm and has the ability of automatically learning. It uses self-learning to enhance the experience and dynamic classification capabilities. We use deep learning to improve the intrusion detection rate and reduce the false alarm rate through learning, a denoising AutoEncoder and three-way decisions intrusion detection method AE-3WD is proposed to improve intrusion detection accuracy. In the processing, deep learning AutoEncoder is used to extract the features of high-dimensional data by combining the coefficient penalty and reconstruction loss function of the encode layer during the training mode. A multi-feature space can be constructed by multiple feature extractions from AutoEncoder, and then a decision for intrusion behavior or normal behavior is made by three-way decisions. NSL-KDD data sets are used to the experiments. The experiment results prove that our proposed method can extract meaningful features and effectively improve the performance of intrusion detection.

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Cite This Article

APA Style
Li, Y., Li, C., Li, Y., Zhang, S. (2022). A new intrusion detection algorithm AE-3WD for industrial control network. Journal of New Media, 4(4), 205-217. https://doi.org/10.32604/jnm.2022.034778
Vancouver Style
Li Y, Li C, Li Y, Zhang S. A new intrusion detection algorithm AE-3WD for industrial control network. J New Media . 2022;4(4):205-217 https://doi.org/10.32604/jnm.2022.034778
IEEE Style
Y. Li, C. Li, Y. Li, and S. Zhang "A New Intrusion Detection Algorithm AE-3WD for Industrial Control Network," J. New Media , vol. 4, no. 4, pp. 205-217. 2022. https://doi.org/10.32604/jnm.2022.034778



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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