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 ...

Researchers at Google’s Threat Intelligence Group (GTIG) have discovered that hackers are creating malware that can harness the power of large language models (LLMs) to rewrite itself on the fly. An ...

The South Atlantic Anomaly, a huge weak spot in the geomagnetic field off South America, has expanded and sprouted a lobe in the direction of Africa over the past decade. When you purchase through ...

Abstract: This paper explores the problem of Generalist Anomaly Detection (GAD), aiming to train one single detection model that can generalize to detect anomalies in diverse datasets from different ...

Introduction: Recent advances in artificial intelligence have created opportunities for medical anomaly detection through multimodal learning frameworks. However, traditional systems struggle to ...

Introduction: Precision agriculture relies on advanced technologies to optimize crop protection and resource utilization, ensuring sustainable and efficient farming practices. Anomaly detection plays ...

Kinil Doshi is a Senior VP at Citibank and a fintech expert in banking compliance and risk management with two decades of experience. In this article, I want to explore AI applications in fraud ...

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 ...

This repository contains the code implementation for the ICSE SEIP 2025 paper titled "Anomaly Detection in Large-Scale Cloud Systems: An Industry Case and Dataset." The preprint for the paper is ...