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9 de jun. de 2022 · ¿Qué es un Anomaly Detection System (Sistema de Detección de Anomalías)? La detección de anomalías requiere una supervisión y un análisis constantes de las métricas de la red. El Sistema de Detección de Anomalías asegura que cuando se detecte algo inesperado y se analice como anomalía, esa información será reportada al ...
22 de jun. de 2021 · In this article, we will try out unsupervised Machine Learning methods of clustering, for grouping hosts in a IP network in to different clusters based on the similarity in their IP addresses.
15 de jul. de 2003 · In this paper, we first review these anomaly detection methods and then describe in detail a statistical signal processing technique based on abrupt change detection. We show that this signal processing technique is effective at detecting several network anomalies.
2 de jul. de 2018 · Amaral et al. proposed a feature-based anomaly detection system using both IP Flow properties and a graph representation in order to carry out a deep inspection of network traffic. The detection is based on the Tasallis entropy, a generalization of Shannon entropy.
In this study, we propose an anomaly-detection method based on time-series traffic flows. First, we decompose superimposed traffic flows into individual flows using our implemented system called the Fast xFlow Proxy, which can decompose traffic flows to a fine granularity.
Anomaly detection, also known as outlier detection, identifies data objects or patterns that deviate from a dataset’s normal behavior. Regardless of whether it’s used for cybersecurity, marketing, or medical purposes, anomaly detection is governed by two basic principles: Anomalies are rare occurrences.
The developed approaches in the current paper are evaluated by testing their efficiency against a real-time network attack using available open-source network tools. The results of the experiment demonstrate successful identification of anomalous instances from the telemetry data with a low false alarm rate.
