Nature

Intrusion Detection Systems and Anomaly Detection Techniques

Intrusion Detection Systems (IDS) and anomaly detection techniques underpin modern cybersecurity by autonomously monitoring network activities and flagging deviations from normal behaviour. IDS are ...
Nature

Sequential Hypothesis Testing and Anomaly Detection

Sequential hypothesis testing is a methodological framework that systematically evaluates data as it is acquired, enabling decisions to be made as soon as sufficient evidence is collected. This ...
Visual Studio Magazine

Anomaly Detection Using K-Means Clustering with JavaScript

Dr. James McCaffrey presents a complete end-to-end demonstration of anomaly detection using k-means data clustering, ...
TechCrunch

Financial firms should leverage machine learning to make anomaly detection easier

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 ...
EurekAlert!

Real-time damage detection in structural health monitoring via reinforcement learning

A novel real-time automated damage detection method leveraging reinforcement learning has been unveiled in a recent study published in Engineering. The research, spearheaded by Chengwen Zhang, Qing ...