Devdiscourse

Fast and Accurate Water Leak Detection in Distribution Networks Using Deep Anomaly Models

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

Data Anomaly Detection Using a Neural Autoencoder with C#

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 ...
Visual Studio Magazine

Autoencoder Anomaly Detection Using PyTorch

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 ...
Security Boulevard

AI-Driven Anomaly Detection in Post-Quantum Context Streams

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.
insideHPC

Research Highlights: MIT Develops First Generative Model for Anomaly Detection that Combines both Reconstruction-based and Prediction-based Models

Kalyan Veeramachaneni and his team at the MIT Data-to-AI (DAI) Lab have developed the first generative model, the AutoEncoder with Regression (AER) for time series anomaly detection, that combines ...
CSOonline

What is anomaly detection? Behavior-based analysis for cyber threats

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 ...