Discover how to secure AI orchestration workflows using post-quantum cryptography and AI-driven anomaly detection for Model ...

Abstract: Detecting anomalies in general ledger data is of utmost importance to ensure the trustworthiness of financial records. Financial audits increasingly rely on machine learning (ML) algorithms ...

Western capital markets are undergoing a structural realignment as defense technology investment reached $49.1 billion in 2025 1, with institutional capital rotating into platforms designed to secure ...

Social media algorithms change constantly, making it hard to maintain consistent reach and engagement. This article breaks ...

There's plenty of buzz around how AI can make self-healing networks a reality -- but how close are we to that, really?

Editor's note: This article (originally published Aug. 13, 2025) has been updated to include new text and illustrations ...

We might be witnessing the start of a new computing era where AI, cloud and quantum begin to converge in ways that redefine data processing and problem-solving.

Welcome. This repository contains the data and scripts which comprise the Numenta Anomaly Benchmark (NAB) v1.1. NAB is a novel benchmark for evaluating algorithms for anomaly detection in streaming, ...

Due to the complexity of hotel operation processes, abnormal situations are inevitable, making proactive anomaly prediction essential for ensuring operational stability. Although current deep learning ...

Advanced fraud detection system using machine learning to identify fraudulent transactions and activities. This project implements multiple machine learning algorithms including Random Forest, XGBoost ...

Cloud infrastructure anomalies cause significant downtime and financial losses (estimated at $2.5 M/hour for major services). Traditional anomaly detection methods fail to capture complex dependencies ...