Deep learning for cybersecurity in smart grids: Review and perspectives

J Ruan, G Liang, J Zhao, H Zhao, J Qiu… - Energy Conversion …, 2023 - Wiley Online Library
Protecting cybersecurity is a non‐negotiable task for smart grids (SG) and has garnered
significant attention in recent years. The application of artificial intelligence (AI), particularly …

Optimal control and communication strategies in multi-energy generation grid

MW Khan, G Li, K Wang, M Numan… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
Multi-energy generation grids (MEGGs) provide a promising solution for reliable operations
of cooperative various distributed energy resources (DERs), supply environmentally friendly …

Resilient load frequency control of islanded AC microgrids under concurrent false data injection and denial-of-service attacks

S Hu, X Ge, X Chen, D Yue - IEEE Transactions on Smart Grid, 2022 - ieeexplore.ieee.org
Due to malicious cyber attacks, the frequency regulation of an islanded microgrid (MG) with
load changes and wind/solar power fluctuations may not be guaranteed and the overall …

Deep reinforcement learning for smart grid operations: algorithms, applications, and prospects

Y Li, C Yu, M Shahidehpour, T Yang… - Proceedings of the …, 2023 - ieeexplore.ieee.org
With the increasing penetration of renewable energy and flexible loads in smart grids, a
more complicated power system with high uncertainty is gradually formed, which brings …

[HTML][HTML] A review on machine learning techniques for secured cyber-physical systems in smart grid networks

MK Hasan, RA Abdulkadir, S Islam, TR Gadekallu… - Energy Reports, 2024 - Elsevier
The smart grid (SG) is an advanced cyber-physical system (CPS) that integrates power grid
infrastructure with information and communication technologies (ICT). This integration …

Generalized graph neural network-based detection of false data injection attacks in smart grids

A Takiddin, R Atat, M Ismail, O Boyaci… - … on Emerging Topics …, 2023 - ieeexplore.ieee.org
False data injection attacks (FDIAs) pose a significant threat to smart power grids. Recent
efforts have focused on developing machine learning (ML)-based defense strategies against …

Autonomous vehicles: The cybersecurity vulnerabilities and countermeasures for big data communication

A Algarni, V Thayananthan - Symmetry, 2022 - mdpi.com
The possible applications of communication based on big data have steadily increased in
several industries, such as the autonomous vehicle industry, with a corresponding increase …

A critical overview of industrial internet of things security and privacy issues using a layer-based hacking scenario

AH Eyeleko, T Feng - IEEE Internet of Things Journal, 2023 - ieeexplore.ieee.org
We have witnessed significant technological advancement over the past few years,
including the Internet of Things (IoT). The IoT's ability to connect consumer appliances to the …

The Role of Deep Learning in Advancing Proactive Cybersecurity Measures for Smart Grid Networks: A Survey

N Abdi, A Albaseer, M Abdallah - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
As smart grids (SGs) increasingly rely on advanced technologies like sensors and
communication systems for efficient energy generation, distribution, and consumption, they …

Optimal injection attack strategy for nonlinear cyber-physical systems based on iterative learning

S Gao, H Zhang, C Huang, Z Wang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
This paper aims to investigate the security problem of nonlinear cyber-physical systems
(CPSs), which poses a challenge to handle compared with linear CPSs. A series of …