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

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.

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

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.

AI methods are increasingly being used to improve grid reliability. Physics-informed neural networks are highlighted as a ...

With 82% of data breaches involving the human element, the digital landscape remains fragile despite billions spent on ...

As leaders begin implementing biometrics, passkeys and AI threat detection, there are several core design principles they ...

Srinubabu Kilaru said Bringing version control and CI/CD into data pipelines changed how quickly we could respond to policy ...

With an evolving nature of cyber threats accelerating at a speed considered too quick to be processed by most establishments, ...

Multimodal Learning, Deep Learning, Financial Statement Analysis, LSTM, FinBERT, Financial Text Mining, Automated Interpretation, Financial Analytics Share and Cite: Wandwi, G. and Mbekomize, C. (2025 ...

Banks will leverage Explainable AI (XAI) tools like SHAP and LIME to demystify complex models, making AI-driven decisions and ...

The old mechanisms to prevent the spread of nuclear weapons are too antiquated and have lost their meaning with the coming of ...