Anomalies are rare observations (eg, data records or events) that deviate significantly from
the others in the sample. Over the past few decades, research on anomaly mining has …

Predictive maintenance is an essential aspect of microgrid operations as it enables
identifying potential equipment failures in advance, reducing downtime, and increasing the …

The smart grid integrates Information and Communication Technologies (ICT) into the
traditional power grid to manage the generation, distribution, and consumption of electrical …

An intrusion detection system (IDS) is an important protection instrument for detecting
complex network attacks. Various machine learning (ML) or deep learning (DL) algorithms …

Abstract The Smart Grid's objective is to increase the electric grid's dependability, security,
and efficiency through extensive digital information and control technology deployment. As a …

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 …

The growing evolution of cyber-attacks imposes a risk in network services. The search of
new techniques is essential to detect and classify dangerous attacks. In that regard, deep …

This research introduces a theoretical framework for network anomaly detection in
cybersecurity, emphasizing the integration of adaptive machine learning models, ensemble …

Cyber attacks are growing with the rapid development and wide use of internet technology.
Botnet attack emerged as one of the most harmful attacks. Botnet identification is becoming …

In many developed countries, the usage of artificial intelligence (AI) and machine learning
(ML) has become important in paving the future path in how data is managed and secured in …