Leveraging Deep Learning to Strengthen the Cyber-Resilience of Renewable Energy Supply Chains: A Survey

MN Halgamuge - IEEE Communications Surveys & Tutorials, 2024 - ieeexplore.ieee.org
Deep learning shows immense potential for strengthening the cyber-resilience of renewable
energy supply chains. However, research gaps in comprehensive benchmarks, real-world …

Mitigating IEC-60870-5-104 vulnerabilities: Anomaly detection in smart grid based on LSTM autoencoder

S Sathar, S Al-Kuwari, A Albaseer… - 2023 International …, 2023 - ieeexplore.ieee.org
Advanced Information Communication Technology (ICT) is used in smart grid systems to
introduce intelligence and efficiency, potentially outperforming conventional power systems …

Double-edged defense: Thwarting cyber attacks and adversarial machine learning in iec 60870-5-104 smart grids

H Teryak, A Albaseer, M Abdallah… - IEEE Open Journal …, 2023 - ieeexplore.ieee.org
Smart grids (SGs), a cornerstone of modern power systems, facilitate efficient management
and distribution of electricity. Despite their advantages, increased connectivity and reliance …

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 (SG) increasingly rely on advanced technologies like sensors and
communication systems for efficient energy generation, distribution, and consumption, they …

Explainable Artificial Intelligence for Crowd Forecasting Using Global Ensemble Echo State Networks

C Samarajeewa, D De Silva, M Manic… - IEEE Open Journal …, 2024 - ieeexplore.ieee.org
Crowd monitoring is a primary function in diverse industrial domains, such as smart cities,
public transport, and public safety. Recent advancements in low-energy devices and rapid …

FedPot: A Quality-Aware Collaborative and Incentivized Honeypot-Based Detector for Smart Grid Networks

A Albaseer, N Abdi, M Abdallah… - … on Network and …, 2024 - ieeexplore.ieee.org
Honeypot technologies provide an effective defense strategy for the Industrial Internet of
Things (IIoT), particularly in enhancing the Advanced Metering Infrastructure's (AMI) security …

Detection of cyber-attacks on smart grids using improved VGG19 deep neural network architecture and Aquila optimizer algorithm

AA Mhmood, Ö Ergül, J Rahebi - Signal, Image and Video Processing, 2024 - Springer
This study introduces an innovative smart grid (SG) intrusion detection system, integrating
Game Theory, swarm intelligence, and deep learning (DL) to protect against complex cyber …

Real-Time Simulation of a Resilient Control Center for Inverter-Based Microgrids

M Beikbabaei, A Mehrizi-Sani - arXiv preprint arXiv:2405.07106, 2024 - arxiv.org
The number of installed remote terminal units (RTU) is on the rise, increasing the
observability and control of the power system. RTUs enable sending data to and receiving …

Gated Tri-Tower Transformer (GT3)-An Inflated Power Generation Attack Detector for Microgrids

TY Syu, TT Kuo, CY Lin - 2023 IEEE International Conference …, 2023 - ieeexplore.ieee.org
Renewable energy microgrids are flourishing due to the rising environmental
consciousness. Blockchain technology is considered a promising solution for advanced …

A Review on Prediction of Solar Energy using Artificial Neural Network.

RK Budania, R Badadapure - Grenze International Journal …, 2024 - search.ebscohost.com
Global acceptance of sustainable development and renewable energy is rising as a result of
climate change's growing effect on national and local governments. The EU 2030 agenda …