Network World

Pure Storage targets AI complexity with a unified data cloud, Azure integration, and embedded security

New features unveiled at Pure//Accelerate promise easier cloud migration, smarter Kubernetes ops, and built-in threat ...
IEEE

DADN: A Dynamic Anomaly Detection Network for Multivariate Time Series Data of the Industrial Internet of Things

Abstract: Industrial Internet of Things (IIoT) faces significant security challenges such as data privacy and vulnerabilities. Unsupervised anomaly detection aims to identify abnormal patterns by ...
IEEE

Detectability Driven Recommendation of Anomaly Detection Models for Time-Series Data

Abstract: Anomaly detection for time-series data has been viewed widely in many practical applications and caused lots of research interests. A popular solution based on deep learning techniques is ...
GitHub

Unsupervised Anomaly Detection in Multivariate Time Series across Heterogeneous Domains

The widespread adoption of digital services, along with the scale and complexity at which they operate, has made incidents in IT operations increasingly more likely, diverse, and impactful. This has ...
GitHub

Diffusion-Scheduled Denoising Autoencoders for Anomaly Detection (AnoDDAE)

This repository provides reproducible implementation of the anomaly detection method based on a denoising autoencoder architecture with diffusion noise scheduling mechanism inspired by diffusion ...
MassDevice

iRhythm data highlights increased AFib detection with Zio long-term continuous monitoring

iRhythm (Nasdaq: IRTC) + today announced findings from a study of its Zio long-term continuous monitoring (LTCM) service. Outcomes from the Oxford University-led active monitoring for atrial ...