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Intrusion Detection in Software De ned Networks with Self-organized Maps, Journal of Telecommunications and Information Technology, 2015, nr 4
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Title: Intrusion Detection in Software De ned Networks with Self-organized Maps, Journal of Telecommunications and Information Technology, 2015, nr 4

Creator:

Amanowicz, Marek ; Jankowski, Damian

Date:

2015, nr 4

Resource Type:

artykuł

Description:

The Software Defined Network (SDN) architecture provides new opportunities to implement security mechanisms in terms of unauthorized activities detection. At the same time, there are certain risks associated with this technology. The presented approach covers a conception of the measurement method, virtual testbed and classification mechanism for SDNs. The paper presents a measurement method which allows collecting network traffic flow parameters, generated by a virtual SDN environment. The collected dataset can be used in machine learning methods to detect unauthorized activities.

Publisher:

National Institute of Telecommunications

Format:

application/pdf

Resource Identifier:

ISSN 1509-4553, on-line: ISSN 1899-8852 ; oai:bc.itl.waw.pl:1873

Source:

Journal of Telecommunications and Information Technology

Language:

ang

Rights Management:

Biblioteka Naukowa Instytutu Łączności

Subject and keywords:

machine learning network simulation network security virtualization IDS dataset metasploit open flow

Object collections:

Last modified:

Feb 20, 2024

In our library since:

Feb 23, 2016

Number of object content hits:

50 157

All available object's versions:

https://ribes-54.man.poznan.pl/publication/2142

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Edition name Date
Amanowicz, Marek, 2015, nr 4, Intrusion Detection in Software De ned Networks with Self-organized Maps, Journal of Telecommunications and Information Technology, 2015, nr 4 Feb 20, 2024

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