A complete technical design document including model selection, training procedures, and detailed architecture diagrams for both training and online detection components. A machine learning model and ...

The new United Nations Institute for Disarmament Research (UNIDR) Intrusion Path framework is designed to analyze both malicious and security activities in the ICT environment. It aims to help UN ...

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The role of cybersecurity tools in anomaly detection. Although predicated on advanced math concepts, anomaly detection, or as the NIST Cybersecurity Framework 2.0 calls it, “adverse event ...

Anomaly detection is sometimes called outlier detection. There are several techniques that can be used for anomaly detection. This article explains how to perform anomaly detection using LightGBM.

To address this need, we propose a novel framework based on unsupervised machine learning for early anomaly detection in AMS circuits. The proposed approach involves injecting anomalies at various ...

Explore the power of AI in anomaly detection, diving into the different approaches used and some real-world use cases. Learn how AI uncovers hidden patterns in data and improves detection of anomalies ...

The intrusion of foreign objects in tracks, one of the sources of injuries and fatalities in metro stations, can be solved as an anomaly detection task. However, the existing anomaly detection methods ...

Since a considerable amount of information is collected during attempted intrusions, intrusion methods can, in effect, be learned, bolstering intrusion prevention methods. There are two approaches to ...