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

.blurhash-client-img { display: none !important; }

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

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

Journal RSS Feed

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,

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.

Previous article Volume 13 (2023): Issue 4 (October 2023)Next article