Cybersecurity challenges in IoT-based smart renewable energy

A Rekeraho, DT Cotfas, PA Cotfas, TC Bălan… - International Journal of …, 2024 - Springer
Abstract The Internet of Things (IoT) makes it possible to collect data from, and issue
commands to, devices via the Internet, eliminating the need for humans in the process while …

Detection of Man-in-the-Middle (MitM) Cyber-Attacks in Oil and Gas Process Control Networks Using Machine Learning Algorithms

UO Obonna, FK Opara, CC Mbaocha, JKC Obichere… - Future Internet, 2023 - mdpi.com
Recently, the process control network (PCN) of oil and gas installation has been subjected
to amorphous cyber-attacks. Examples include the denial-of-service (DoS), distributed …

Anomaly detection in smart grid using optimized extreme gradient boosting with SCADA system

A Sharma, R Tiwari - Electric Power Systems Research, 2024 - Elsevier
The significance of anomaly detection is paramount for ensuring the security and better cost-
efficiency of smart grids. The extensive installation of advanced metering infrastructure (AMI) …

A novel approach detection for IIoT attacks via artificial intelligence

G Karacayılmaz, H Artuner - Cluster Computing, 2024 - Springer
Abstract The Industrial Internet of Things (IIoT) is a paradigm that enables the integration of
cyber-physical systems in critical infrastructures, such as power grids, water distribution …

An AI-Based Real-time Intrusion Detection System for Power Electronics-Dominated Grid: Attack on Inverters PQ Set-Points

A Zadehgol-Mohammadi, M Baker… - 2023 IEEE Energy …, 2023 - ieeexplore.ieee.org
This work presents a long short-term memory (LSTM) neural network based method for real-
time detection of intruded power setpoints of grid-following inverters (GFLIs) in power …