[HTML][HTML] Analysis of cyber security attacks and its solutions for the smart grid using machine learning and blockchain methods
Smart grids are rapidly replacing conventional networks on a worldwide scale. A smart grid
has drawbacks, just like any other novel technology. A smart grid cyberattack is one of the …
has drawbacks, just like any other novel technology. A smart grid cyberattack is one of the …
[HTML][HTML] Prospects and challenges of the machine learning and data-driven methods for the predictive analysis of power systems: A review
W Strielkowski, A Vlasov, K Selivanov, K Muraviev… - Energies, 2023 - mdpi.com
The use of machine learning and data-driven methods for predictive analysis of power
systems offers the potential to accurately predict and manage the behavior of these systems …
systems offers the potential to accurately predict and manage the behavior of these systems …
[HTML][HTML] Review of cybersecurity analysis in smart distribution systems and future directions for using unsupervised learning methods for cyber detection
In a physical microgrid system, equipment failures, manual misbehavior of equipment, and
power quality can be affected by intentional cyberattacks, made more dangerous by the …
power quality can be affected by intentional cyberattacks, made more dangerous by the …
[HTML][HTML] A review on machine learning techniques for secured cyber-physical systems in smart grid networks
The smart grid (SG) is an advanced cyber-physical system (CPS) that integrates power grid
infrastructure with information and communication technologies (ICT). This integration …
infrastructure with information and communication technologies (ICT). This integration …
A two-stage cyber attack detection and classification system for smart grids
As the adoption of Internet of Things (IoT) devices increases rapidly, industrial applications
of IoT devices gain further popularity. Some of these applications, such as smart grids, are …
of IoT devices gain further popularity. Some of these applications, such as smart grids, are …
[HTML][HTML] A proficient ZESO-DRKFC model for smart grid SCADA security
Smart grids are complex cyber-physical systems that incorporate smart devices'
communication capabilities into the grid to enable remote management and the control of …
communication capabilities into the grid to enable remote management and the control of …
[HTML][HTML] Machine Learning: Models, Challenges, and Research Directions
T Talaei Khoei, N Kaabouch - Future Internet, 2023 - mdpi.com
Machine learning techniques have emerged as a transformative force, revolutionizing
various application domains, particularly cybersecurity. The development of optimal …
various application domains, particularly cybersecurity. The development of optimal …
An overview of reinforcement learning-based approaches for smart home energy management systems with energy storages
The paper's state-of-the-art review focuses on an in-depth evaluation of smart home energy
management systems which employ reinforcement learning-based methods to integrate …
management systems which employ reinforcement learning-based methods to integrate …
Densely connected neural networks for detecting denial of service attacks on smart grid network
TT Khoei, N Kaabouch - 2022 IEEE 13th Annual Ubiquitous …, 2022 - ieeexplore.ieee.org
Smart grid has several benefits, including efficiency and reliability. However, this network is
prone to several cyber-attacks and has limited security. One of the main damaging attacks …
prone to several cyber-attacks and has limited security. One of the main damaging attacks …
DAMGAT Based Interpretable Detection of False Data Injection Attacks in Smart Grids
False data injection attacks (FDIAs) significantly disrupt the secure operation of smart grids
by manipulating the measured values collected by intelligent instruments. Existing studies …
by manipulating the measured values collected by intelligent instruments. Existing studies …