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Erschienen in: Cluster Computing 1/2019

20.02.2018

Design of network threat detection and classification based on machine learning on cloud computing

verfasst von: Hyunjoo Kim, Jonghyun Kim, Youngsoo Kim, Ikkyun Kim, Kuinam J. Kim

Erschienen in: Cluster Computing | Sonderheft 1/2019

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Abstract

To respond to recent network threats that are using increasingly intelligent techniques, the intelligent security technology on cloud computing is required. Especially it supports small and medium enterprises to build IT security solution with low cost and less effort because it is provided as Security as a Service on a cloud environment. In this paper, we particularly propose the network threat detection and classification method based on machine learning, which is a part of the intelligent threat analysis technology. In order to improve the performance of detection and classification of network threat, it was built in a hybrid way such as applying an unsupervised learning approach with unlabeled data, naming clusters with labeled data, and using a supervised learning approach for feature selection.

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Metadaten
Titel
Design of network threat detection and classification based on machine learning on cloud computing
verfasst von
Hyunjoo Kim
Jonghyun Kim
Youngsoo Kim
Ikkyun Kim
Kuinam J. Kim
Publikationsdatum
20.02.2018
Verlag
Springer US
Erschienen in
Cluster Computing / Ausgabe Sonderheft 1/2019
Print ISSN: 1386-7857
Elektronische ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-018-1841-8

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