Journal
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
Volume 22, Issue -, Pages 2341-2350Publisher
SPRINGER
DOI: 10.1007/s10586-018-1841-8
Keywords
Network threat detection and classification; Security as a Service; Machine learning; Cloud computing; Virtual security function
Funding
- Institute for Information & communications Technology Promotion (IITP) - Korea government (MSIP) [2016-0-00078]
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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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