Anomaly detection algorithms are leading the charge to take organizations away from the limitations of manually monitoring datasets. In its place is a wave of solutions that can not only make use of ...

The number of real-life, high-value use cases for AI anomaly detection have grown a lot over the years and are expected to continue to rise. Advances in artificial intelligence (AI) are ...

Anomaly detection is the process of finding and identifying point, contextual or collective anomalies that fall outside the bounds of defined policies. Detection itself is only the first step; further ...

This is anomaly detection at play. Engineers, scientists and technologists have historically counted on anomaly detection to prevent industrial accidents, stop financial fraud, intervene early to ...

What does anomaly detection actually mean? Find out inside PCMag's comprehensive tech and computer-related encyclopedia.

Anomaly Detection – Unsupervised Approach Following its etymology, an anomaly is any deviation from a rule. Consequently any violation of the standard behavior traced in historical data can be ...

Anomaly detection is an important AI tool, analyzing time-series data for items that are outside normal operating characteristics for the data source.

An anomaly is a violation of expectancy. However, the analytical community uses it to describe statistical outliers, which misses the cognitive dimension.

ML driven anomaly detection is a new and powerful tool that will help companies quickly analyze the volume of transactions in real-time. That minimizes risk and maximized potential revenue.

Does network behavior anomaly detection provide a true security solution against viruses and worms? Two experts in the field debate the issue in this week’s Face-off.