TechRepublic

Network Anomaly Detection : Methods, Systems and Tools

Network anomaly detection is an important and dynamic research area. Many Network Intrusion Detection methods and Systems (NIDS) have been proposed in the literature. In this paper, the authors ...
Business Wire

Numenta Anomaly Benchmark Evaluates Anomaly Detection Techniques for Real-time, Streaming Data

REDWOOD CITY, Calif.--(BUSINESS WIRE)--Numenta, Inc., a leader in machine intelligence, today launched the Numenta Anomaly Benchmark (NAB), an open-source benchmark and tool designed to help data ...
techtimes

Securing API Gateway with AI/Ml-Driven Anomaly Detection & Mitigation

Are you aware that your API gateway, a vital component of modern software architecture, is also one of the most vulnerable points in a network? Shockingly, a 2022 survey by Statista revealed that most ...
Scientific Research Publishing

Graph Neural Networks for Anomaly Detection in Cloud Infrastructure ()

Graph Neural Networks for Anomaly Detection in Cloud Infrastructure ...
Nature

Intrusion Detection Systems and Anomaly Detection Techniques

Intrusion Detection Systems (IDS) and anomaly detection techniques underpin modern cybersecurity by autonomously monitoring network activities and flagging deviations from normal behaviour. IDS are ...
datanami.com

Chung-Ang University Researchers Review Deep Learning-based Methods to Detect Time Series Data Anomaly

SEOUL, Feb. 9, 2023 — Monitoring financial security, industrial safety, medical conditions, climate, and pollution require analysis of large volumes of time series data. A crucial step in this ...
Visual Studio Magazine

Data Anomaly Detection Using a Neural Autoencoder with C#

Data anomaly detection is 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. There are many different types of ...
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 ...