Feasibility Study of Semi-supervised Intrusion Detection Systems for Industrial Control Systems-Reference-Cited by-同舟云学术

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Feasibility Study of Semi-supervised Intrusion Detection Systems for Industrial Control Systems

Published:2024-04-17 Issue: Volume:19 Page:166-168
ISSN:
Container-title:2024 10th International Conference on Applied System Innovation (ICASI)
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Author:

Loo Fu-Nie¹,Chen Tung-Shou¹,Tsai Chia-Wei¹,Lin Jason²,Yang Chun-Wei³

Affiliation:

1. National Taichung University of Science and Technology,Department of Computer Science and Information Engineering,Taichung City,Taiwan,404

2. National Chung Hsing University,Department of Computer Science and Engineering,Taichung City,Taiwan,402202

3. China Medical University,Master Program for Digital Health Innovation,Taichung City,Taiwan,406040

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10547719/10547721/10547975.pdf?arnumber=10547975

Reference15 articles.

1. A Machine Learning Approach for Anomaly Detection in Industrial Control Systems Based on Measurement Data

2. Machine Learning-Based Network Vulnerability Analysis of Industrial Internet of Things

3. A Hybrid Multistage DNN-Based Collaborative IDPS for High-Risk Smart Factory Networks

4. Adversarial attacks on machine learning cybersecurity defences in Industrial Control Systems

5. Effective Industrial Internet of Things Vulnerability Detection Using Machine Learning

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