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 ...

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.

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

Discover how AI-driven anomaly detection safeguards post-quantum context streams in Model Context Protocol (MCP) environments, ensuring robust security for AI infrastructure against future threats.

A good way to see where this article is headed is to take a look at the screenshot in Figure 1 and the graph in Figure 2. The demo program begins by loading a tiny 10-item dataset into memory. The ...

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, ...

Researchers from Politecnico di Milano propose a data-driven water leak detection method that treats leaks as anomalies in ...