Innovations like self-supervised learning, federated anomaly detection, and neuromorphic computing promise greater strides.

Machine learning (ML) and artificial intelligence (AI) algorithms have revolutionized anomaly detection, replacing the labor-intensive manual approach with more efficient methods. Now, businesses ...

Although predicated on advanced math concepts, anomaly detection, or as the NIST Cybersecurity Framework 2.0 calls it, “adverse event analysis,” has over the past two decades been incorporated ...

See IDS and anomaly. (2) Detecting data that lie outside the normal range. Also called "outlier detection." THIS DEFINITION IS FOR PERSONAL USE ONLY. All other reproduction requires permission.

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 ...

Azure Cognitive Services enters a new AI area Fortunately, the first new cognitive service to explore other aspects of machine learning entered beta recently: adding anomaly detection to the roster.

Despite its promise, AI-driven anomaly detection still faces challenges. Potential biases in AI models and the need for large, high-quality datasets must be addressed to ensure accurate findings. The ...