[HTML][HTML] Cybersecurity in power grids: Challenges and opportunities
Increasing volatilities within power transmission and distribution force power grid operators
to amplify their use of communication infrastructure to monitor and control their grid. The …
to amplify their use of communication infrastructure to monitor and control their grid. The …
[HTML][HTML] Cyber threats to smart grids: Review, taxonomy, potential solutions, and future directions
Smart Grids (SGs) are governed by advanced computing, control technologies, and
networking infrastructure. However, compromised cybersecurity of the smart grid not only …
networking infrastructure. However, compromised cybersecurity of the smart grid not only …
Fault diagnosis based on extremely randomized trees in wireless sensor networks
Abstract Wireless Sensor Network (WSN) being highly diversified cyber–physical system
makes it vulnerable to numerous failures, which can cause devastation towards safety …
makes it vulnerable to numerous failures, which can cause devastation towards safety …
Exploring the power of machine learning to predict carbon dioxide trapping efficiency in saline aquifers for carbon geological storage project
Carbon geological sequestration (CGS) in saline aquifers is an effective carbon utilization
approach to decrease the effect of greenhouse gases on the atmosphere. However, the …
approach to decrease the effect of greenhouse gases on the atmosphere. However, the …
Machine learning for cybersecurity in smart grids: A comprehensive review-based study on methods, solutions, and prospects
Abstract In modern Smart Grids (SGs) ruled by advanced computing and networking
technologies, condition monitoring relies on secure cyberphysical connectivity. Due to this …
technologies, condition monitoring relies on secure cyberphysical connectivity. Due to this …
[HTML][HTML] Security risk modeling in smart grid critical infrastructures in the era of big data and artificial intelligence
Smart grids (SG) emerged as a response to the need to modernize the electricity grid. The
current security tools are almost perfect when it comes to identifying and preventing known …
current security tools are almost perfect when it comes to identifying and preventing known …
Detecting stealthy false data injection attacks in the smart grid using ensemble-based machine learning
Stealthy false data injection attacks target state estimation in energy management systems
in smart power grids to adversely affect operations of the power transmission systems. This …
in smart power grids to adversely affect operations of the power transmission systems. This …
FDI attack detection using extra trees algorithm and deep learning algorithm-autoencoder in smart grid
SH Majidi, S Hadayeghparast, H Karimipour - International Journal of …, 2022 - Elsevier
Today's smart grid (SG) combines the classical power system with the information
technology, leading to a cyber-physical system (CPS). Its strong dependencies on digital …
technology, leading to a cyber-physical system (CPS). Its strong dependencies on digital …
[HTML][HTML] A deep learning methodology for predicting cybersecurity attacks on the internet of things
OA Alkhudaydi, M Krichen, AD Alghamdi - Information, 2023 - mdpi.com
With the increasing severity and frequency of cyberattacks, the rapid expansion of smart
objects intensifies cybersecurity threats. The vast communication traffic data between …
objects intensifies cybersecurity threats. The vast communication traffic data between …
Novel machine learning algorithms to predict the groundwater vulnerability index to nitrate pollution at two levels of modeling
The accurate mapping and assessment of groundwater vulnerability index are crucial for the
preservation of groundwater resources from the possible contamination. In this research …
preservation of groundwater resources from the possible contamination. In this research …