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Fast Attack Detection Method for Imbalanced Data in Industrial Cyber-Physical Systems Cover

Fast Attack Detection Method for Imbalanced Data in Industrial Cyber-Physical Systems

Journal of Artificial Intelligence and Soft Computing Research
Volume 13 (2023): Issue 4 (October 2023)
By: Meng Huang,  Tao Li,  Beibei Li,  Nian Zhang and  Hanyuan Huang  
Open Access
|Oct 2023
Authors

Authors

Meng Huang

School of Cyber Science and Engineering, Sichuan University, Chengdu, China
College of Computer Science and Engineering, Chongqing Three Gorges University, China

Tao Li

School of Cyber Science and Engineering, Sichuan University, Chengdu, China

Beibei Li

libeibei@scu.edu.cn

School of Cyber Science and Engineering, Sichuan University, Chengdu, China

Nian Zhang

Departmnt of Electrical and Computer Engineering, University of the District of Columbia, Washington, USA

Hanyuan Huang

School of Cyber Science and Engineering, Sichuan University, Chengdu, China
DOI: https://doi.org/10.2478/jaiscr-2023-0017
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Language: English
Page range: 229 - 245
Submitted on: May 5, 2023
Accepted on: Sep 11, 2023
Published on: Oct 30, 2023
Published by: SAN University
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
intrusion detection system,
industrial cyber-physical Systems,
imbalanced data,
all k-nearest neighbor,
LightGBM.
Related subjects:
Computer sciences,
Databases and data mining,
Artificial intelligence

© 2023 Meng Huang, Tao Li, Beibei Li, Nian Zhang, Hanyuan Huang, published by SAN University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Volume 13 (2023): Issue 4 (October 2023)
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