A review of anomaly detection strategies to detect threats to cyber-physical systems
N Jeffrey, Q Tan, JR Villar - Electronics, 2023 - mdpi.com
Cyber-Physical Systems (CPS) are integrated systems that combine software and physical
components. CPS has experienced rapid growth over the past decade in fields as disparate …
components. CPS has experienced rapid growth over the past decade in fields as disparate …
The role of machine learning in network anomaly detection for cybersecurity
A Yaseen - Sage Science Review of Applied Machine …, 2023 - journals.sagescience.org
This research introduces a theoretical framework for network anomaly detection in
cybersecurity, emphasizing the integration of adaptive machine learning models, ensemble …
cybersecurity, emphasizing the integration of adaptive machine learning models, ensemble …
Machine learning and deep learning for user authentication and authorization in cybersecurity: A state-of-the-art review
In the continuously developing field of cyber security, user authentication and authorization
play a vital role in protecting personal information and digital assets from unauthorized use …
play a vital role in protecting personal information and digital assets from unauthorized use …
Digital twin-based intrusion detection for industrial control systems
Digital twins have recently gained significant interest in simulation, optimization, and
predictive maintenance of Industrial Control Systems (ICS). Recent studies discuss the …
predictive maintenance of Industrial Control Systems (ICS). Recent studies discuss the …
[PDF][PDF] Industrial datasets with ICS testbed and attack detection using machine learning techniques
Industrial control systems (ICS) are the backbone for the implementation of cybersecurity
solutions. They are susceptible to various attacks, due to openness in connectivity …
solutions. They are susceptible to various attacks, due to openness in connectivity …
One-Dimensional Convolutional Wasserstein Generative Adversarial Network Based Intrusion Detection Method for Industrial Control Systems
Z Cai, H Du, H Wang, J Zhang, Y Si, P Li - Electronics, 2023 - mdpi.com
The imbalance between normal and attack samples in the industrial control systems (ICSs)
network environment leads to the low recognition rate of the intrusion detection model for a …
network environment leads to the low recognition rate of the intrusion detection model for a …
[PDF][PDF] Improving Method of Anomaly Detection Performance for Industrial IoT Environment.
Industrial Control System (ICS), which is based on Industrial IoT (IIoT), has an intelligent
mobile environment that supports various mobility, but there is a limit to relying only on the …
mobile environment that supports various mobility, but there is a limit to relying only on the …
Building the Operational Technology (OT) Cybersecurity Workforce: What are Employers Looking for?
CA Ramezan, PM Coffy… - Journal of …, 2023 - digitalcommons.kennesaw.edu
A trained workforce is needed to protect operational technology (OT) and industrial control
systems (ICS) within national critical infrastructure and critical industries. However, what …
systems (ICS) within national critical infrastructure and critical industries. However, what …
CyberSCADA Network Security Analysis Model for Intrusion Detection Systems in the Smart Grid
CyberSCADA is a soft target for industrial cyber attackers. The success of such attacks on
the Smart Grid can be devastating owing to the countless processes and systems that …
the Smart Grid can be devastating owing to the countless processes and systems that …
Exploring the power of convolutional neural networks for encrypted industrial protocols recognition
E Holasova, P Blazek, R Fujdiak, J Masek… - … Energy, Grids and …, 2024 - Elsevier
The main objective of this paper is to classify unencrypted and encrypted industrial protocols
using deep learning, especially Convolutional Neural Networks. Protocol recognition is …
using deep learning, especially Convolutional Neural Networks. Protocol recognition is …