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Neural Computing and Applications

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01.01.2015 | Original Article

Data mining-based integrated network traffic visualization framework for threat detection

verfasst von: Amit Kumar Bhardwaj, Maninder Singh

Erschienen in: Neural Computing and Applications | Ausgabe 1/2015

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Abstract

In this speedy and voluminous digital world, the threat detection and reporting are a challenging job for rapid action. The present study deals with a strong and viable solution to overcome different threats, network security using data mining approach and techniques through visual graphical representation. Current research study explained and proposed a novel approach named as ‘integrated network traffic visualization system’. Nevertheless, current framework is working and based on data mining, further help out to demonstrates two new visualization schemes called as: Firstly Grid and secondly Platter. Per framework results, the Grid view is capable of displaying network traffic in different classified grids, based on application layer protocols. Additionally, Platter view visualizes campus area wireless network traffic on a single screen mechanized automatically adjusted with network size. These active schemes are significantly effective to identify and monitor the compromised machines and cuts down reaction time.

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Titel: Data mining-based integrated network traffic visualization framework for threat detection
verfasst von: Amit Kumar Bhardwaj
Maninder Singh
Publikationsdatum: 01.01.2015
Verlag: Springer London
Erschienen in: Neural Computing and Applications / Ausgabe 1/2015
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-014-1701-2

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