[HTML][HTML] A novel hybrid ensemble learning for anomaly detection in industrial sensor networks and SCADA systems for smart city infrastructures
YK Saheed, OH Abdulganiyu, TA Tchakoucht - Journal of King Saud …, 2023 - Elsevier
Abstract Critical Infrastructures (CIs) use Supervisory Control and Data Acquisition (SCADA)
systems for monitoring and remote control. Sensor networks are being integrated into all …
systems for monitoring and remote control. Sensor networks are being integrated into all …
Cyber vulnerabilities of energy systems
In an era characterized by extensive use of and reliance on information and communications
technology (ICT), cyber–physical power systems (CPPSs) have emerged as a critical …
technology (ICT), cyber–physical power systems (CPPSs) have emerged as a critical …
[HTML][HTML] Enhancing wind power prediction with self-attentive variational autoencoders: A comparative study
Accurate wind power prediction is critical for efficient grid management and the integration of
renewable energy sources into the power grid. This study presents an effective deep …
renewable energy sources into the power grid. This study presents an effective deep …
Identification and classification for multiple cyber attacks in power grids based on the deep capsule CNN
Cyber-attacks have become one of the main threats to the security, reliability, and economic
operation of power systems. Detection and classification of multiple cyber-attacks pose …
operation of power systems. Detection and classification of multiple cyber-attacks pose …
Semi-supervised deep learning-driven anomaly detection schemes for cyber-attack detection in smart grids
Modern power systems are continuously exposed to malicious cyber-attacks. Analyzing
industrial control system (ICS) traffic data plays a central role in detecting and defending …
industrial control system (ICS) traffic data plays a central role in detecting and defending …
[HTML][HTML] SCADA securing system using deep learning to prevent cyber infiltration
Abstract Supervisory Control and Data Acquisition (SCADA) systems are computer-based
control architectures specifically engineered for the operation of industrial machinery via …
control architectures specifically engineered for the operation of industrial machinery via …
Multi-stage learning framework using convolutional neural network and decision tree-based classification for detection of DDoS pandemic attacks in SDN-based …
Supervisory Control and Data Acquisition (SCADA) systems, which play a critical role in
monitoring, managing, and controlling industrial processes, face flexibility, scalability, and …
monitoring, managing, and controlling industrial processes, face flexibility, scalability, and …
Adaptive Deep Reinforcement Learning Algorithm for Distribution System Cyber Attack Defense With High Penetration of DERs
With grid modernization, smart inverters are increasingly used to execute advanced controls
for distribution network reliability. However, this also increases the cyber-attack space. This …
for distribution network reliability. However, this also increases the cyber-attack space. This …
Improved semi-supervised data-mining-based schemes for fault detection in a grid-connected photovoltaic system
Fault detection is a necessary component to perform ongoing monitoring of photovoltaic
plants and helps in their safety, maintainability, and productivity with the desired …
plants and helps in their safety, maintainability, and productivity with the desired …
Attack detection using artificial intelligence methods for SCADA security
Technological developments and transformations have rapidly risen since the Fourth
Industrial Revolution. The prevalence of industrial devices interconnected over the wireless …
Industrial Revolution. The prevalence of industrial devices interconnected over the wireless …