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Secure data warehousing in ERP environments: An AI-based multimodal threat detection framework
In an era where data has become one of the most valuable assets for organizations, protecting that data is a strategic ...
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.
Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Vivek Yadav, an engineering manager from ...
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, ...
Dr. James McCaffrey from Microsoft Research presents a complete program that uses the Python language LightGBM system to create a custom autoencoder for data anomaly detection. You can easily adapt ...
Researchers in Slovakia have demonstrated a machine-learning framework that predicts PV inverter output and detects anomalies using only electrical and temporal data, achieving 100% accuracy in ...
Dr. James McCaffrey of Microsoft Research provides full code and step-by-step examples of anomaly detection, used to find items in a dataset that are different from the majority for tasks like ...
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