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A DDoS Attack Detection Method Based on SVM in Software Defined Network
Joint Authors
Ye, Jin
Cheng, Xiangyang
Zhu, Jian
Feng, Luting
Song, Ling
Source
Security and Communication Networks
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-04-24
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Information Technology and Computer Science
Abstract EN
The detection of DDoS attacks is an important topic in the field of network security.
The occurrence of software defined network (SDN) (Zhang et al., 2018) brings up some novel methods to this topic in which some deep learning algorithm is adopted to model the attack behavior based on collecting from the SDN controller.
However, the existing methods such as neural network algorithm are not practical enough to be applied.
In this paper, the SDN environment by mininet and floodlight (Ning et al., 2014) simulation platform is constructed, 6-tuple characteristic values of the switch flow table is extracted, and then DDoS attack model is built by combining the SVM classification algorithms.
The experiments show that average accuracy rate of our method is 95.24% with a small amount of flow collecting.
Our work is of good value for the detection of DDoS attack in SDN.
American Psychological Association (APA)
Ye, Jin& Cheng, Xiangyang& Zhu, Jian& Feng, Luting& Song, Ling. 2018. A DDoS Attack Detection Method Based on SVM in Software Defined Network. Security and Communication Networks،Vol. 2018, no. 2018, pp.1-8.
https://search.emarefa.net/detail/BIM-1214586
Modern Language Association (MLA)
Ye, Jin…[et al.]. A DDoS Attack Detection Method Based on SVM in Software Defined Network. Security and Communication Networks No. 2018 (2018), pp.1-8.
https://search.emarefa.net/detail/BIM-1214586
American Medical Association (AMA)
Ye, Jin& Cheng, Xiangyang& Zhu, Jian& Feng, Luting& Song, Ling. A DDoS Attack Detection Method Based on SVM in Software Defined Network. Security and Communication Networks. 2018. Vol. 2018, no. 2018, pp.1-8.
https://search.emarefa.net/detail/BIM-1214586
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1214586