Microsoft

When configuration becomes a vulnerability: Exploitable misconfigurations in AI apps

Exposed UIs, weak authentication, and risky defaults could turn cloud-native AI apps on Kubernetes into potential targets by ...
IEEE

Anomaly Detection in Network Traffic Using Advanced Machine Learning Techniques

Abstract: Anomaly detection in network traffic is a critical aspect of network security, particularly in defending against the increasing sophistication of cyber threats. This study investigates the ...
GitHub

Ralph for Claude Code

Ralph is an implementation of the Geoffrey Huntley's technique for Claude Code that enables continuous autonomous development cycles he named after Ralph Wiggum. It enables continuous autonomous ...
GitHub

MultiADS: Defect-aware Supervision for Multi-type Anomaly Detection and Segmentation in Zero-Shot Learning (ICCV2025)

This software is a research prototype, solely developed for and published as part of the publication MultiADS: Defect-aware Supervision for Multi-type Anomaly Detection and Segmentation in Zero-Shot ...
IEEE

Anomaly Detection in Industrial Internet of Things: A Graph Learning Approach With Spatiotemporal Interactions

Abstract: In real-world industrial activities, large industrial systems typically have complex network structures composed of multiple devices, where the operating status of devices is reflected by ...