Doug Bonderud is an award-winning writer capable of bridging the gap between complex and conversational across technology, innovation and the human condition. By defining a set of normal user and ...

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 ...

Explore how AI-driven anomaly detection enhances the security of Model Context Protocol (MCP) deployments, protecting AI infrastructure from evolving threats with real-time insights.

Anomaly detection can be powerful in spotting cyber incidents, but experts say CISOs should balance traditional signature-based detection with more bespoke methods that can identify malicious activity ...

What is explainable AI (XAI)? What are some of the use cases for XAI? What are the technology requirements for implementing XAI? Anomaly detection is the process of identifying when something deviates ...

Explore strategies for managing combinatorial explosion in high dimensional anomaly detection to enhance data observability ...

The NDR market is expanding due to increased cloud, remote work, and IoT adoption, creating complex attack surfaces. Opportunities include AI-driven anomaly detection, integration with EDR, XDR, SIEM, ...

Unlike pattern-matching, which is about spotting connections and relationships, when we detect anomalies we are seeing disconnections—things that do not fit together. Anomalies get much less attention ...

Data anomaly detection is 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. There are many different types of ...