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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.
1 de jun. de 2012 · These fields will help identify if there is an anomaly occurring in network traffic without digging deep into the packet payload and patterns. We know how address and port are connected to call it a socket, but how can we devise a simple yet effective measure on the basis of flags.
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.
Anomaly detection techniques can identify critical issues like website hacks, bank or insurance frauds, technical bugs, network errors, structural malfunctions, and business-altering changes in customer behavior.
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.
5 de sept. de 2017 · Anomaly-based intrusion detection is pursued using the chi-square technique on various network protocol parameters. It has four detection methodologies, viz., traffic capturing, signature-based detection, network access policy violation, and protocol anomaly detection as a part of its network sensor.
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.
