A Deep Multi-Modal Cyber-Attack Detection in Industrial Control Systems
Author:
Affiliation:
1. Schulich School of Engineering, University of Calgary,Calgary,Canada
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10143075/10143030/10143147.pdf?arnumber=10143147
Reference30 articles.
1. Physical layer attack identification and localization in cyber–physical grid: An ensemble deep learning based approach
2. Machine Learning-Based Network Vulnerability Analysis of Industrial Internet of Things
3. Multilayer Data-Driven Cyber-Attack Detection System for Industrial Control Systems Based on Network, System, and Process Data
4. A Self-tuning Cyber-Attacks Location Identification Approach for Industrial Internet of Things
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1. An Intelligent Big Data Security Framework Based on AEFS-KENN Algorithms for the Detection of Cyber-Attacks from Smart Grid Systems;Big Data Mining and Analytics;2024-06
2. An improved autoencoder-based approach for anomaly detection in industrial control systems;Systems Science & Control Engineering;2024-04-18
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