A survey on IoT-enabled smart grids: emerging, applications, challenges, and outlook

A Goudarzi, F Ghayoor, M Waseem, S Fahad, I Traore - Energies, 2022 - mdpi.com
Swift population growth and rising demand for energy in the 21st century have resulted in
considerable efforts to make the electrical grid more intelligent and responsive to …

Advancements and challenges in machine learning: A comprehensive review of models, libraries, applications, and algorithms

S Tufail, H Riggs, M Tariq, AI Sarwat - Electronics, 2023 - mdpi.com
In the current world of the Internet of Things, cyberspace, mobile devices, businesses, social
media platforms, healthcare systems, etc., there is a lot of data online today. Machine …

Machine learning for cybersecurity in smart grids: A comprehensive review-based study on methods, solutions, and prospects

T Berghout, M Benbouzid, SM Muyeen - International Journal of Critical …, 2022 - Elsevier
Abstract In modern Smart Grids (SGs) ruled by advanced computing and networking
technologies, condition monitoring relies on secure cyberphysical connectivity. Due to this …

Data-driven next-generation smart grid towards sustainable energy evolution: techniques and technology review

F Ahsan, NH Dana, SK Sarker, L Li… - … and Control of …, 2023 - ieeexplore.ieee.org
Meteorological changes urge engineering communities to look for sustainable and clean
energy technologies to keep the environment safe by reducing CO 2 emissions. The …

Cyber threats to smart grids: Review, taxonomy, potential solutions, and future directions

J Ding, A Qammar, Z Zhang, A Karim, H Ning - Energies, 2022 - mdpi.com
Smart Grids (SGs) are governed by advanced computing, control technologies, and
networking infrastructure. However, compromised cybersecurity of the smart grid not only …

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 …

Securing the Industrial Internet of Things against ransomware attacks: A comprehensive analysis of the emerging threat landscape and detection mechanisms

M Al-Hawawreh, M Alazab, MA Ferrag… - Journal of Network and …, 2023 - Elsevier
Due to the complexity and diversity of Industrial Internet of Things (IIoT) systems, which
include heterogeneous devices, legacy and new connectivity protocols and systems, and …

Impact, vulnerabilities, and mitigation strategies for cyber-secure critical infrastructure

H Riggs, S Tufail, I Parvez, M Tariq, MA Khan, A Amir… - Sensors, 2023 - mdpi.com
Several critical infrastructures are integrating information technology into their operations,
and as a result, the cyber attack surface extends over a broad range of these infrastructures …

Machine learning in cybersecurity: A review of threat detection and defense mechanisms

UI Okoli, OC Obi, AO Adewusi… - World Journal of Advanced …, 2024 - wjarr.com
The cybersecurity concerns get increasingly intricate as the digital world progresses. In light
of the increasing complexity of cyber threats, it is imperative to develop and implement …

[HTML][HTML] An information security model for an IoT-enabled Smart Grid in the Saudi energy sector

A Akkad, G Wills, A Rezazadeh - Computers and Electrical Engineering, 2023 - Elsevier
Data supply and transmission in the Smart Grid achieve better sensing, control, information
communication and sharing, and more rational decision-making. An Internet of Things …