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

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 Secur...

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Bibliographic Details
Published in:Cluster computing 2019-01, Vol.22 (Suppl 1), p.2341-2350
Main Authors: Kim, Hyunjoo, Kim, Jonghyun, Kim, Youngsoo, Kim, Ikkyun, Kim, Kuinam J.
Format: Article
Language:English
Subjects:
Algorithms
Classification
Cloud computing
Clustering
Computer Communication Networks
Computer Science
Controllers
Cybersecurity
Data mining
Datasets
Machine learning
Malware
Open source software
Operating Systems
Processor Architectures
Ransomware
Security services
Small & medium sized enterprises-SME
Supervised learning
Technology assessment
Threat evaluation
Threats
Unsupervised learning
User interface
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Summary: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.
ISSN:1386-7857
1573-7543
DOI:10.1007/s10586-018-1841-8