Researchers in Morocco analyzed cybersecurity challenges in smart grids, highlighting AI-driven detection and defense strategies against threats like distributed denial-of-service, false data ...
Anomaly detection is one of the more difficult and underserved operational areas in the asset-servicing sector of financial institutions. Broadly speaking, a true anomaly is one that deviates from the ...
An international research team developed a multi-stage intrusion detection system that uses supervised and unsupervised AI techniques to detect and mitigate cyber threats in smart renewable energy ...
Principal Developer Janmejaya Mishra explores how AI and machine learning are advancing predictive intelligence systems ...
The increasing complexity of modern chemical engineering processes presents significant challenges for timely and accurate anomaly detection. Traditional ...
Scientists in Spain have implemented recursive least squares (RLS) algorithms for anomaly detection in PV systems and have found they can provide “more realistic and meaningful assessment” than ...
Dr. James McCaffrey of Microsoft Research tackles the process of examining a set of source data to find data items that are different in some way from the majority of the source items. Data anomaly ...
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